Articles de revues : « PLANNING ADAPTIVE METHODOLOGY »

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Zhang, P., J. Liang et D. Yan. « Evaluation of Online Image Guided Adaptive Inverse Planning Methodology ». International Journal of Radiation Oncology*Biology*Physics 69, n^o 3 (novembre 2007) : S641—S642. http://dx.doi.org/10.1016/j.ijrobp.2007.07.1980.

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Solis Barreto, Priscila, et Paulo Henrique Portela de Carvalho. « A Planning and Adaptive Routing Methodology for Multimedia Networks ». IEEE Latin America Transactions 7, n^o 6 (décembre 2009) : 673–80. http://dx.doi.org/10.1109/tla.2009.5419365.

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Zussman, E., et M. Zhou. « A methodology for modeling and adaptive planning of disassembly processes ». IEEE Transactions on Robotics and Automation 15, n^o 1 (1999) : 190–94. http://dx.doi.org/10.1109/70.744614.

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Greipel, J., D. Ortiz Sarceño et R. Prof Schmitt. « Adaptive Prüfplanung für Kleinserien*/Adaptive inspection planning for small series ». wt Werkstattstechnik online 107, n^o 11-12 (2017) : 780–85. http://dx.doi.org/10.37544/1436-4980-2017-11-12-4.

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In der Kleinserienproduktion ist eine 100 %-Prüfung üblich. Eine kostengünstigere Stichprobenprüfung ist nicht anwendbar, da produzierte Lose nicht die nötige Datenanzahl aufweisen. Um sie zu erhöhen und die Stichprobenprüfung anwendbar zu machen, können ähnliche Produktmerkmale mit einem Gruppierungsalgorithmus zusammengefasst werden. Darauf aufbauend wird eine Methodik zur Erstellung eines adaptiven Prüfplans für Kleinserien vorgestellt, angewendet und der weitere Forschungsbedarf dargestellt.   In small series production, 100 % inspection is common practice. A more cost-effective sampling inspection is not applicable as batches produced do not provide the necessary amount of data. To increase the amount of data and allow for sampling inspection, similar product features can be grouped by a grouping algorithm. Thus, a methodology is presented for designing an adaptive sampling plan for small batch production while further research requirements are discussed.

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Tamar Begdarashvili, Tamar Begdarashvili. « Methodology for Developing an Adaptive Business Plan ». Economics 105, n^o 4-5 (8 mai 2022) : 253–59. http://dx.doi.org/10.36962/ecs105/4-5/2022-253.

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Any firm has to adapt to a changing business environment to operate successfully. In the 21st century, they have to work actively on adaptive business plans and have some long-term plans, as the degree of uncertainty in the business environment increases steadily while the adaptive competencies help the firm to develop a competitive advantage over the environment. We can talk a lot to describe the business landscape of the last decade, however the only thing that can be said with certainty is that during this period there have never been certain, obvious radical changes. As business cycles and processes in the world become more rapidly accelerated, we can more strongly criticize the traditional strategic planning process, which offers small alternatives of business scenarios and focuses less on radical changes in market demand. Against this background, we want to focus on the importance of developing an adaptive business plan and discuss its development methodology for firms. Keywords: Adaptation, Business Plan, Adaptive Management, Adaptive Measures Complex, Competitive Advantage.

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Hudec, Oto. « Cities of Resilience : Integrated Adaptive Planning ». Quality Innovation Prosperity 21, n^o 1 (30 avril 2017) : 106. http://dx.doi.org/10.12776/qip.v21i1.776.

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Purpose: to classify the definitions and approaches towards the concept of the city of resilience, to understand the reciprocal influences of academic research, resilience assessments and planning results as well as to identify the inconsistencies and formulate future research directions.Methodology/Approach: explanatory analysis, literature-based work comparing definitions, principles, dimensions. Rationalised analytic reasoning and approaches which lead to formulating crucial research questions.Findings: the definitions of city resilience are classified according to objects and fields. The differentiations in the sustainability and resilience concepts are indicated and an adaptive planning framework is described.Research Limitation/implication: the main challenges are filling in the gap between the theory and practice of city resilience literature, dealing with the complexity, the implementation of complexity theory considering self-organisation.Originality/Value of paper: the analysis contributes to the clarification of the main concept, classification of the main approaches and the formulation of open research questions and future trends.

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Kataev, M. Yu, A. A. Sukhorukov et L. A. Bulysheva. « Network planning methodology in the problem of adaptive learning of university students ». Informatics and education, n^o 8 (23 novembre 2020) : 45–56. http://dx.doi.org/10.32517/0234-0453-2020-35-8-45-56.

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The article proposes a methodology of network planning in the problem of adaptive learning of university students. The elements of network planning are briefly presented, the use of adaptive learning methods in the educational process is described. The learning process in the university is considered, and the possibilities of describing it using the formalism of network planning within some discipline are analyzed. The developed technique for assessing the performance of tasks is given. The process of interaction between a teacher and a student in the learning process is described in terms of assessing the sequence of this interaction and the parameters of the proposed algorithm. The developed model of the discipline in the form of a linear sequence of actions for the study of the discipline is presented. To reflect the efforts made to obtain a learning outcome, a graphical representation of the discipline's network model is given. The results of the use of network graphics in the educational process within one discipline are presented. The formulas used to assess the student when using this technique are described. Several variants of passing the academic discipline by a student are considered, analytical data obtained by comparing these variants are presented. A computer program designed to support the developed technique is presented. The results of using the proposed methodology for assessing the study of a discipline by a university student are analyzed. The study of the methodology presented in the article can be useful for both university teachers and students.

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Suh, Daniel, et Megan S. Ryerson. « Frameworks for Adaptive Airport Planning and Techniques for a New Era of Planning ». Transportation Research Record : Journal of the Transportation Research Board 2603, n^o 1 (janvier 2017) : 65–77. http://dx.doi.org/10.3141/2603-07.

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Airport planners, in determining the long-term development of an airport's infrastructure, estimate future use of the airport by using two loose categories of methods: ( a) peer group learning and ( b) forecasting. In peer group learning, airport planners compare their airports with like airports and engage in peer-to-peer exchange of information about lessons learned from past experiences and technical and planning guidance. The blend of quantitative and qualitative methodologies can be a powerful tool for airport planners because the planners can validate their forecasts with the actual experiences at similar airports. In the current state of the aviation industry, airport planners must engage in peer group learning because the environment in which they are planning their airports is more volatile than it was previously; however, while forecasting has been well studied by scholars and airport planners, peer group learning has attracted relatively less attention. Given the role of peer group learning in airport planning, airport planners must pay careful attention to how they define their peers in ever-evolving economic and industrial environments. Since deregulation of the airline industry in the 1970s, the airport system has become much more nuanced and is no longer easily defined, while airport planners often resort to single metrics such as enplanements as a peer criterion. This study developed and tested a peer identification methodology that reflects volatilities in the economy and the airport industry by using an expanded list of both static and dynamic metrics. This methodology highlights an important lesson that metrics matter in the ways in which airports identify their peers, benchmark their performance, and help to improve their plans.

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Emelianova, Daria, Natalia Kliuchareva, Sergey Kolesnichenko-Yanushev et Andrey Yakovlev. « Organization of standardization work planning in an industrial enterprise ». E3S Web of Conferences 164 (2020) : 10013. http://dx.doi.org/10.1051/e3sconf/202016410013.

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The paper considers the methodology for organizing information support planning at the main stages of a product life cycle. If used, the methodology will help minimize risks of counteragents’ non-compliance with contractual obligations. The research study is aimed at substantiating the ways, techniques, and methods of building an effective information support management system of an enterprise through creating an adaptive system for standardization work planning. When preparing the materials suggested in the paper, such scientific research methods were used as: analyzing the information needs of an enterprise, simulating a short-term information support planning process, pooling the experience in organizing standardization work in industrial enterprises involved in sin-gle-piece and serial production, as well as the principles of consistency and comprehensiveness of information support planning. As a result of the conducted research study, the following ones are proposed: a methodology for forming a Standardization Action Plan in an enterprise (organization); ways and methods for adapting the Standardization Action Plan to changing production conditions; ways to monitor the realization of actions envisaged in the Plan; the rules for evaluating the effectiveness of the information support system of an enterprise. The general methodology of information support relies on a principle of building quality management systems that implement the Deming Cycle.

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Sulistiawan, Andi, et Melkior Nikolar Ngalumsine Sitokdana. « Information System Strategic Planning in PT XYZ Using Wetherbe's Methodology ». TEPIAN 1, n^o 3 (18 août 2020) : 103–10. http://dx.doi.org/10.51967/tepian.v1i3.168.

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Along with the development of technology in business, PT XYZ, which is engaged in the food industry, which is located in Sidomukti, Salatiga City is required to be adaptive and innovative by utilizing the availability of information technology. In order to win the competition, and information system strategic plan is needed to support the implementation of information technology and information systems in terms of operations as well as for strategic ones. Therefore, this research conducted by making strategic planning of information systems for use at PT XYZ using the Wetherbe methodology. This methodology is considered as an appropriate approach tool for the company. The solution for information system requirements is based on the strategic planning analysis that has been carried out, namely, producing nine information systems consisting of one information system to be developed from existing applications and eight information systems for the proposed application. And IT personnel are needed for the database and network server work or to carry out proper training for each employee so that if there is damage to the system and infrastructure it can be directly handled. This was done due to the condition of the number of human resources and limited funds for the strategic planning of information systems.

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Al Younes, Younes Al, et Martin Barczyk. « Adaptive Nonlinear Model Predictive Horizon Using Deep Reinforcement Learning for Optimal Trajectory Planning ». Drones 6, n^o 11 (27 octobre 2022) : 323. http://dx.doi.org/10.3390/drones6110323.

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This paper presents an adaptive trajectory planning approach for nonlinear dynamical systems based on deep reinforcement learning (DRL). This methodology is applied to the authors’ recently published optimization-based trajectory planning approach named nonlinear model predictive horizon (NMPH). The resulting design, which we call `adaptive NMPH’, generates optimal trajectories for an autonomous vehicle based on the system’s states and its environment. This is done by tuning the NMPH’s parameters online using two different actor-critic DRL-based algorithms, deep deterministic policy gradient (DDPG) and soft actor-critic (SAC). Both adaptive NMPH variants are trained and evaluated on an aerial drone inside a high-fidelity simulation environment. The results demonstrate the learning curves, sample complexity, and stability of the DRL-based adaptation scheme and show the superior performance of adaptive NMPH relative to our earlier designs.

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Ataeva, A. G. « Problems of developing a strategic planning methodology for regional socio-economic systems ». Upravlenie 7, n^o 4 (27 janvier 2020) : 90–99. http://dx.doi.org/10.26425/2309-3633-2019-4-90-99.

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The issues of the methodology for developing regional strategies have been considered in three aspects: firstly, from the position of restrictions on the use of traditional strategic planning schools in relation to the regional socio-economic systems; secondly, in the context of the characteristics of the region as an object of strategic planning; thirdly, taking into account modern realities of information technology development and management decision-making tools. It has been it has been revealed, that traditional strategic management schools take into account only a certain aspect of strategizing and have limited application for regional systems. The peculiarities of the region have been have been disclosed as an open complex system, occupying an intermediate level in the public administration system, characterized by a non-linear development and informational openness of management.The complex nature of a region affects the fact, that a regional strategy is a mechanism for coordinating the long-term interests of various stakeholders of a territory. This happens both through their participation in determining strategic priorities and selecting specific strategic projects at the goal setting stage, and through the use of special model tools, which are characterized by the presence of built-in interaction loops for different classes of economic situations and allowing them to adapt their resource strategies while agreeing on common goals of functioning. It has been ascertained, that the current stage of economic development is characterized by features related to the development of information technologies and management decision-making tools, which determines the need to expand the methodological and methodical base of the regional strategic planning.In total, the analysis shows, that in the context of the adaptive behavior of economic agents of the region, the uncertain external and internal environment, traditional methodological approaches and methodical tools become of little use in the actual practice of regional governance. The effective direction of improving the methods of strategic planning in these conditions is the use of adaptive management and simulation modeling technologies based on modern information technologies.

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Schlegl, Honold, Leistner, Albrecht, Roth, Leistner, Binz et Sobek. « Integration of LCA in the Planning Phases of Adaptive Buildings ». Sustainability 11, n^o 16 (8 août 2019) : 4299. http://dx.doi.org/10.3390/su11164299.

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The high consumption of resources in the building industry requires a significant reduction of material in buildings and consequently a reduction of emissions over all phases of the life cycle. This is the aim of the Collaborative Research Centre 1244 Adaptive Skins and Structures for the Built Environment of Tomorrow, funded by the German Research Foundation (DFG), which addresses research on the development and integration of adaptive systems in building structures and skins. New approaches in building planning are required for the implementation of adaptive buildings. Therefore, a multidisciplinary team from various fields such as architecture, civil and mechanical engineering, and system dynamics is necessary. The environmental impacts of the whole life cycle have to be considered for an integral planning process for adaptive buildings right from the beginning. For the integration of the Life Cycle Assessment (LCA), four temporal and content-related interfaces were identified in the planning process. Inputs and outputs of the LCA were defined for the relevant planning stages in order to enable the greatest possible benefit for the planners and to minimize the environmental impacts as far as possible. The result of the research work is a methodology that can be used in the future to reduce life cycle-related environmental impacts in the planning process of adaptive buildings (ReAdapt).

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Morales-Alzate, Luis Fernando, Clara Solano-Vanegas, Angela Carrillo-Ramos, Jairo Montoya-Torres, Ramon Fabregat et Jaime A. Pavlich-Mariscal. « Accomm : adaptive system for supply network operational planning ». International Journal of Web Information Systems 14, n^o 1 (16 avril 2018) : 78–106. http://dx.doi.org/10.1108/ijwis-02-2017-0010.

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Purpose This paper aims to present Accomm a software implementation of Ágora-SN, a supply network (SN) customer-oriented model integrated with an Adaptation Model. Accomm serves two purposes: as an experimental validation tool to measure the impact of Adaptation on an agribusiness SN model and as a logistic and marketing operations planning assistant. Design/methodology/approach The design of Accomm is based on the results of the Ágora-SN model that comprises the following tasks: to characterize the SN actors’ processes ( composed of multiple first-tier suppliers, a focal company and multiple first-tier customers), identifying the ones oriented to the customer; to integrate these processes into a SN model which incorporates a supplier cooperation model; and to provide an adaptation model that implements a customer profile and a context profile to improve order fulfillment. Findings To validate the Ágora-SN model, a prototype Accomm was created referred to a real Colombian agribusiness sector company, specifically in the floriculture sector. This prototype was validated through two methods: a usability scale and a set of scenarios that compared the application’s behavior with and without adaptation and cooperation. The application provides a better response to demand when both adaptation and cooperation are enabled. Research limitations/implications This work was tested in an academic environment and was validated by different experts. Further tests in operational real-life environments are required to fully validate the approach. Originality/value The main contribution of this work is the integration of Adaptation into a SN model as a way to center the SN toward the customer. As an additional contribution, the validation tool Accomm is conceived as an operational planning tool for agribusiness SN.

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Li, Xiao, Hongtai Cheng et Xiaoxiao Liang. « Adaptive motion planning framework by learning from demonstration ». Industrial Robot : the international journal of robotics research and application 46, n^o 4 (17 juin 2019) : 541–52. http://dx.doi.org/10.1108/ir-10-2018-0216.

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Purpose Learning from demonstration (LfD) provides an intuitive way for non-expert persons to teach robots new skills. However, the learned motion is typically fixed for a given scenario, which brings serious adaptiveness problem for robots operating in the unstructured environment, such as avoiding an obstacle which is not presented during original demonstrations. Therefore, the robot should be able to learn and execute new behaviors to accommodate the changing environment. To achieve this goal, this paper aims to propose an improved LfD method which is enhanced by an adaptive motion planning technique. Design/methodology/approach The LfD is based on GMM/GMR method, which can transform original off-line demonstrations into a compressed probabilistic model and recover robot motion based on the distributions. The central idea of this paper is to reshape the probabilistic model according to on-line observation, which is realized by the process of re-sampling, data partition, data reorganization and motion re-planning. The re-planned motions are not unique. A criterion is proposed to evaluate the fitness of each motion and optimize among the candidates. Findings The proposed method is implemented in a robotic rope disentangling task. The results show that the robot is able to complete its task while avoiding randomly distributed obstacles and thereby verify the effectiveness of the proposed method. The main contributions of the proposed method are avoiding unforeseen obstacles in the unstructured environment and maintaining crucial aspects of the motion which guarantee to accomplish a skill/task successfully. Originality/value Traditional methods are intrinsically based on motion planning technique and treat the off-line training data as a priori probability. The paper proposes a novel data-driven solution to achieve motion planning for LfD. When the environment changes, the off-line training data are revised according to external constraints and reorganized to generate new motion. Compared to traditional methods, the novel data-driven solution is concise and efficient.

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Vertakova, Yulia, Tatyana Babich et Olga Lebedenko. « Use of public-private partnership for the implementation of innovative urban policy and formation of the adaptive territory ». Economic Annals-ХХI 186, n^o 11-12 (28 décembre 2020) : 124–33. http://dx.doi.org/10.21003/ea.v186-14.

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The article substantiates the use of public-private partnership (PPP) in order to implement the innovative urban planning policy and create the adaptive territory aimed at the implementation of modern realities of development in the context of technological and social transformation of the economy. The authors of the paper have carried out a comparative analysis of the peculiarities of the implementation of the urban planning policy in individual countries, which made it possible to determine its main innovative directions in modern conditions and form a conceptual basis for the implementation of an innovative urban planning policy based on PPP, a distinctive feature of which is the integrated consideration of factors affecting urban planning activities, as well as the orientation of innovative projects towards the implementation of the adaptive territory approach that meets modern requirements and gives the greatest synergistic effect during its implementation. A comparative analysis of the use of public-private partnership. in urban planning activities in individual countries of the world has been carried out. As a result, an expert analysis methodology for the compliance of the PPP project with the goals and principles of the adaptive territory approach has been substantiated, based on the use of identified priorities for territorial development, a procedure for assessing the contribution of PPP subjects to solving problems of urban planning and calculating a compliance ratio. The proposed methodology makes it possible to comprehensively evaluate the results of the implementation of PPP projects both at the stage of completion and at the stage of project operation.

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Postma, Albert, et Ian Seymour Yeoman. « A systems perspective as a tool to understand disruption in travel and tourism ». Journal of Tourism Futures 7, n^o 1 (1 mars 2021) : 67–77. http://dx.doi.org/10.1108/jtf-04-2020-0052.

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Purpose The purpose of this paper is to contribute to the understanding of systems thinking and its value for strategic foresight and scenario planning to address disruptive forces from the outside, with the outbreak of COVID19 as a case study. Design/methodology/approach This conceptual paper concisely discusses the notion of systems thinking and the concept of complex adaptive systems and puts this in the context of contemporary society in general and travel and tourism in particular. Strategic foresight and scenario planning are introduced as an approach to anticipate disruptions in the complex adaptive travel and tourism system. Findings As COVID-19 has demonstrated, travel and tourism is sensitive for disruptions from the outside. To ensure long-term resilience and sustainability, a systems approach embedded in strategic foresight and scenario planning is emphasised. Practical implications Strategic foresight and scenario planning is a competence that can be learned. Originality/value Given the present status of COVID-19 and other disruptors on travel and tourism, a resilient approach to the future is necessary; thus, the value of this viewpoint paper is the proposition of an adaptive capacity system. This paper offers advice to understand and manage complexity and adaptive systems.

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An, Qing, Qiqi Hu, Ruoli Tang et Lang Rao. « Intelligent Scheduling Methodology for UAV Swarm Remote Sensing in Distributed Photovoltaic Array Maintenance ». Sensors 22, n^o 12 (13 juin 2022) : 4467. http://dx.doi.org/10.3390/s22124467.

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In recent years, the unmanned aerial vehicle (UAV) remote sensing technology has been widely used in the planning, design and maintenance of urban distributed photovoltaic arrays (UDPA). However, the existing studies rarely concern the UAV swarm scheduling problem when applied to remoting sensing in UDPA maintenance. In this study, a novel scheduling model and algorithm for UAV swarm remote sensing in UDPA maintenance are developed. Firstly, the UAV swarm scheduling tasks in UDPA maintenance are described as a large-scale global optimization (LSGO) problem, in which the constraints are defined as penalty functions. Secondly, an adaptive multiple variable-grouping optimization strategy including adaptive random grouping, UAV grouping and task grouping is developed. Finally, a novel evolutionary algorithm, namely cooperatively coevolving particle swarm optimization with adaptive multiple variable-grouping and context vector crossover/mutation strategies (CCPSO-mg-cvcm), is developed in order to effectively optimize the aforementioned UAV swarm scheduling model. The results of the case study show that the developed CCPSO-mg-cvcm significantly outperforms the existing algorithms, and the UAV swarm remote sensing in large-scale UDPA maintenance can be optimally scheduled by the developed methodology.

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Aps, Robert, Kristjan Herkül, Jonne Kotta, Roland Cormier, Kirsi Kostamo, Leena Laamanen, Juho Lappalainen, Külli Lokko, Anneliis Peterson et Riku Varjopuro. « Marine environmental vulnerability and cumulative risk profiles to support ecosystem-based adaptive maritime spatial planning ». ICES Journal of Marine Science 75, n^o 7 (10 août 2018) : 2488–500. http://dx.doi.org/10.1093/icesjms/fsy101.

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Abstract Human use of marine and coastal areas is increasing worldwide, resulting in conflicts between different interests for marine space, overexploitation of marine resources, and environmental degradation. In this study we developed a methodology that combines assessments of marine environmental vulnerability and cumulative human pressures to support the processes of ecosystem-based adaptive maritime spatial planning. The methodology is built on the spatially explicit marine environmental vulnerability profile (EVP) that is an aggregated product of the distribution of essential nature values (habitat-forming benthic macroalgal and invertebrate species, benthic species richness, birds and seals as top marine predators) and their sensitivities to disturbances. The marine environmental cumulative risk profile (ERP) combines the EVP and the HELCOM Baltic Sea Pressure Index (BSPI), the latter representing the spatial distribution of intensities of cumulative anthropogenic pressures. The ERP identifies areas where environmental risks are the highest due to both long recoveries of the biota and high intensities of human pressures. This methodology can be used in any other sea areas by modifying the list of nature values, their sensitivity to disturbances, and the intensities of human pressure.

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Shorikov, Andrey F., et Elena V. Butsenko. « Intelligent software system for optimizing adaptive control of business planning processes ». Journal Of Applied Informatics 15, n^o 89 (30 octobre 2020) : 9–28. http://dx.doi.org/10.37791/2687-0649-2020-15-5-9-28.

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The article describes the functionality developed by the authors of an intelligent software system for optimizing adaptive control of business planning processes in the face of uncertainty. The results are based on a new method for optimizing adaptive project management using network economic and mathematical modeling. Based on this method, a methodology has been developed for solving the problem of optimizing adaptive control of business planning processes, which in the proposed intelligent software decision support system uses a block containing an adaptive control optimization model. As the objective function (evaluation functional) in the method used, the value of the length of the time period for the execution of the business plan, which needs to be minimized, is considered. The method used allows you to create a class of acceptable strategies for adaptive control of the implementation process for the business plan in question. Within the framework of this class of strategies, an optimal adaptive control strategy for the implementation of business planning processes is formed, the optimal time for its implementation and the optimal schedule for implementing the business plan as a whole, and the corresponding optimal adaptive control strategies are calculated. Application of the proposed new method in an intelligent software system allows for feedback and optimal time for the implementation of the business project as a whole. The developed intelligent system is designed to automate the modeling of business planning processes and optimize adaptive decision-making control during their implementation on the basis of network economic and mathematical modeling, as well as methods and tools for developing intelligent soft systems. The created system takes into account the existing specific technical and economic conditions and information support. The results obtained in this work can serve as the basis for creating intelligent instrumental systems for supporting managerial decision-making in the implementation of business planning processes in the face of information uncertainty and risks.

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Kunsch, P., A. Chevalier et J. P. Brans. « Comparing the adaptive control methodology (ACM) to the financial planning practice of a large international group ». European Journal of Operational Research 132, n^o 3 (août 2001) : 479–89. http://dx.doi.org/10.1016/s0377-2217(00)00199-5.

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Carstens, Christoffer, Karin Mossberg Sonnek, Riitta Räty, Per Wikman-Svahn, Annika Carlsson-Kanyama et Jonathan Metzger. « Insights from Testing a Modified Dynamic Adaptive Policy Pathways Approach for Spatial Planning at the Municipal Level ». Sustainability 11, n^o 2 (15 janvier 2019) : 433. http://dx.doi.org/10.3390/su11020433.

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The Dynamic Adaptive Policy Pathways (DAPP) approach has successfully been used to manage uncertainties in large infrastructure projects. However, the viability of the DAPP approach for spatial planning in smaller municipal settings is not clear. This paper examines opportunities and constraints of using adaptive pathways approaches to help small municipalities plan for future sea-level rise. The methodology was based on developing a simplified DAPP-approach, which was tested in a multiple experimental case study of spatial planning projects in three municipalities in Sweden. The results show that the approach promoted vulnerability-based thinking among the end-users and generated new ideas on how to manage the uncertain long-term impacts of future sea-level rise. However, the increased understanding of uncertainties was used to justify static, rather than adaptive, solutions. This somewhat surprising outcome can be explained by perceived legal constraints, lack of experience of adaptive pathways, and unwillingness to prescribe actions that could prove difficult to enforce in the future. More research is needed to further understand at what planning phases dynamic policy pathway approaches work best and how current barriers in legislation, practices, mind-set, organization, and resources can be overcome.

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Korableva, Galina, et Elena Kucherova. « Adaptive method of generation of optimal production orders ». E3S Web of Conferences 110 (2019) : 02127. http://dx.doi.org/10.1051/e3sconf/201911002127.

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The article describes the approach to the generation of production or sales orders for enterprises with ordering planning system. The adaptive method of orders’ generation for production and sales of products is multi-level and includes several stages, allowing forming almost optimal package of applications from consumers, obtained by a mathematical model, the optimization criterion of which is the profit function from product sales. The functional structure of the automated decision support system, which is a tool for implementing an adaptive methodology, is considered. The developed method will reduce energy costs during transportation and storage of production orders.

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Ma, Tengfei, Patrick Ferber, Siyu Huo, Jie Chen et Michael Katz. « Online Planner Selection with Graph Neural Networks and Adaptive Scheduling ». Proceedings of the AAAI Conference on Artificial Intelligence 34, n^o 04 (3 avril 2020) : 5077–84. http://dx.doi.org/10.1609/aaai.v34i04.5949.

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Automated planning is one of the foundational areas of AI. Since no single planner can work well for all tasks and domains, portfolio-based techniques have become increasingly popular in recent years. In particular, deep learning emerges as a promising methodology for online planner selection. Owing to the recent development of structural graph representations of planning tasks, we propose a graph neural network (GNN) approach to selecting candidate planners. GNNs are advantageous over a straightforward alternative, the convolutional neural networks, in that they are invariant to node permutations and that they incorporate node labels for better inference.Additionally, for cost-optimal planning, we propose a two-stage adaptive scheduling method to further improve the likelihood that a given task is solved in time. The scheduler may switch at halftime to a different planner, conditioned on the observed performance of the first one. Experimental results validate the effectiveness of the proposed method against strong baselines, both deep learning and non-deep learning based.The code is available at https://github.com/matenure/GNN_planner.

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Hurina, O., V. Krylenko et I. Novikov. « Forecasting the Main Indicators of Insurance Companies ». Modern Economics 25, n^o 1 (23 février 2021) : 52–57. http://dx.doi.org/10.31521/modecon.v25(2021)-08.

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Abstract. Introduction. Econometric and adaptive models make it possible to predict financial and economic indicators in the short and long term. The most common forecasting models are linear trend models, adaptive Brown, Holt, Holt-Winters, Box-Jenkins, autoregressive and other models. It has been proved that the use of adaptive forecasting models becomes especially relevant in the context of constant changes in the external environment, instability of the economic and political situation. Purpose. The purpose of this article is to substantiate the expediency of using forecasting methods when planning the development of the insurance market and to implement the procedure for forecasting the main indicators of its development using modern methods and techniques. Results. Improving the efficiency of the insurance market is facilitated by the correct organization of its planning and the direct implementation of the planned indicators. Optimality of planning is determined by the degree to which the accuracy of the predicted level of planned indicators is achieved. The methodology and results of the forecast of insurance payments made for the near future can be taken as a basis for drawing up current and strategic plans of insurance companies. Conclusions. It has been established that one of the barriers to the effective development of the insurance market in general and insurance companies in particular is the insufficient level of planning of their activities, especially in terms of forecasting key indicators. The procedure for forecasting the receipt of insurance payments was implemented using modern forecasting methods. The effectiveness of the Brown’s adaptive model for short-term planning of insurance premiums is proved. The proposed model was tested for adequacy, on its basis, recommendations were developed for further application in the practice of insurance companies. Keywords: insurance; insurance market; planning; forecasting; econometric model; adaptive model; trend extrapolation.

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Kulikov, G. G., A. V. Rechkalov et A. V. Artyukhov. « METHODOLOGY OF SYSTEM MODELING OF ADAPTIVE MANAGEMENT OF MACHINE-BUILDING PRODUCTION ». Bulletin of the South Ural State University. Ser. Computer Technologies, Automatic Control & ; Radioelectronics 20, n^o 4 (décembre 2020) : 115–25. http://dx.doi.org/10.14529/ctcr200412.

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The Model Paradigm of digital control in production systems is based on the intelligent integra-tion of virtual and real processes with production objects (their system models). In this case, the platform (environment) for the intelligent integration of virtual and real processes is the information environment of the subject-oriented area. The functions of specialists, in this case, are reduced to the role of experts who implement the formal predicate knowledge prescribed in the corresponding methods and job descriptions (documents) and analyze the updated data of real production from the corresponding databases and knowledge bases. This ensures the properties of identifiability and traceability of production facilities and their processes. The spatial and temporal distribution of the holding's production facilities determine the basic coordinate system for their system modeling and management. Automation of intellectual processes of organization, planning, monitoring and management of interconnected production facilities in space and time, taking into account the in-fluence of the external environment, in real and virtual aspects, is an important and urgent task. System modeling is one of the main components of the organization of any process, including pro-duction. It should also be noted that the system modeling process itself is an intellectual, laborious and ob-jective process. Purpose of the study. To develop a methodology for system modeling (system de-scription) and adaptive management of production activities by individual enterprises as part of a machine-building holding. Develop a methodology for implementing this system model. Research methods used in the work: – principles of system engineering methodology (process approach, life cycle, etc.); – an integrated approach and structural analysis of the diversity of information processes in the interaction of individual production enterprises within the holding; – functional modeling of dynamic systems. Results. A methodology of system modeling (system description) of multilevel adaptive control of production systems distributed in space and time is proposed, taking into account the influence of the external environment. On the example of a machine-building holding, it is shown that this in-tellectualized system dynamic model can be implemented in the form of an Information-Advisory System. Conclusion. The proposed Methodology of System Analysis and Modeling of Adaptive Mana¬gement of Machine-Building Production as a part of the holding allows solving urgent prob-lems of effective management of production activities, taking into account the influence of the ex-ternal environment.

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Flyen, Cecilie, Åshild Lappegard Hauge, Anders-Johan Almås et Åsne Lund Godbolt. « Municipal collaborative planning boosting climate resilience in the built environment ». International Journal of Disaster Resilience in the Built Environment 9, n^o 1 (12 février 2018) : 58–69. http://dx.doi.org/10.1108/ijdrbe-10-2016-0042.

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Purpose A meta-study covering the past decade maps the development of Norwegian municipal planning, climate adaptation and institutional vulnerability towards climate change. This paper aims to explore the implementation of climate adaptive changes in Norwegian legal planning and building framework into municipal practice and policy instruments from 2007 to 2016. The study is planned to answer the question: what drivers ensure increased municipal efforts in their climate adaptive planning and building practice? Design/methodology/approach The paper presents empirical findings from two qualitative research projects, each with nine interviews of municipal key personnel within three municipalities’ planning and building services and an ongoing qualitative, expert interview-based study (eight individual/group interviews). Findings Risk reduction and climate resilience are still unsatisfactorily attended in many Norwegian municipalities. There is a gap between political and administrative levels in communicating bilateral expectations and needs for incorporation of climate adaptive measures. Policy instruments maintaining climate adaptation are in demand by different building process actors. Yet, extreme weather events seem to be the main drivers for actual implementation of climate change aspects into municipal policy instruments. Networking, both within and between municipalities, is an important strategy for learning climate adaptation. Research limitations/implications Both globally and in Norway, the focus on climate change impacts is steadily increasing. Municipal risk and vulnerability analyses are statutory, as is the incorporation of the results into local plans at appropriate levels. Originality/value The originality of this paper is the meta-perspective over the past decade, the qualitative approach and the use of environmental psychology theories.

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Maragno, Denis, Michele Dalla Fontana et Francesco Musco. « Mapping Heat Stress Vulnerability and Risk Assessment at the Neighborhood Scale to Drive Urban Adaptation Planning ». Sustainability 12, n^o 3 (2 février 2020) : 1056. http://dx.doi.org/10.3390/su12031056.

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Climate change is one of the most complex issues of the 21st century, and even though there is general consensus about the urgency of taking action at the city level, the planning and implementation of adaptation measures is advancing slowly. The lack of data and information to support the planning process is often mentioned as a factor hampering the adaptation processes in cities. In this paper, we developed and tested a methodology for heat stress vulnerability and risk assessment at the neighborhood scale to support designers, planners, and decision makers in developing and implementing adaptation strategies and measures at the local level. The methodology combines high-resolution spatial information and crowdsourcing geospatial data to develop sensitivity, adaptive capacity, vulnerability, exposure, and risk indicators. The methodology is then tested on the urban fabric of the city of Padova, Italy. Our results show that different vulnerability and risk values correspond to different typologies of urban areas. Furthermore, the possibility of combining high-resolution information provided by the indicators and land use categories is of great importance to support the adaptation planning process. We also argue that the methodology is flexible enough to be applied in different contexts.

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Luque-Vega, Luis F., Miriam A. Carlos-Mancilla, Verónica G. Payán-Quiñónez et Emmanuel Lopez-Neri. « Smart Cities Oriented Project Planning and Evaluation Methodology Driven by Citizen Perception—IoT Smart Mobility Case ». Sustainability 12, n^o 17 (31 août 2020) : 7088. http://dx.doi.org/10.3390/su12177088.

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Smart Cities empower progress through technology integration directed with a strategic approach to sustainable development and citizen well-being. The creation of solid strategic planning boosts the development of infrastructure, innovation, and technology. However, the above can be compromised if citizens are not properly involved; therefore, it is relevant to enhance citizen participation when a new Smart City project appears on the horizon. This work presents a Smart Cities Oriented Project Planning and Evaluation (SCOPPE) Methodology that combines the citizen participation and the Minimum Viable Product creation through adaptive project management. Moreover, since the smart mobility projects represent the first step towards a Smart City, a case of study of an Intelligent Parking System (SEI-UVM) is presented following the SCOPPE Methodology. The application’s steps results lead us to key and useful information when defining, designing, and implementing the minimum viable product of the cornerstone device of the SEI-UVM: the Smart Vehicle Presence Sensor (SPIN-V). It is worthwhile to mention that the proposed SCOPPE Methodology could be extended to any Smart City project.

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Wang, Qi-Bin, Si-Yang Piao, Ming-Wei Piao, Peng Dang, Qiu-Ze Li et Jing-Ying Ren. « A Dynamic Design Methodology for Large-Scale Complex Nonlinear Systems Based on Orthogonal Decomposition Technique ». Shock and Vibration 2023 (10 janvier 2023) : 1–18. http://dx.doi.org/10.1155/2023/7152223.

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HSRS is taken as a typical research case of large-scale complex nonlinear systems, and the re-innovation of associated imported technologies needs to be combined with the particularities of Chinese HSR practices, seeking a more suitable dynamic design methodology to conduct the self-adaptive improved design. Different from the troublesomeness of the primary hunting phenomenon, the self-adaptive improved design can decrease considerably the impact of car body instability on ride comfort merely by applying the semiactive damping technique between intervehicles, to promote scientifically the limit and construction speeds under the rational conditions of wheel-rail matching, i.e., λeN ≥ λemin, λemin = (0.03–0.05). The researching viewpoint of hunting kinematics makes the investigations on the geometric nonlinearity of the wheel-rail contacts contrary to the hypothesis of small creepage and no spin. Since the technical prototype of German ICE3 serial bogies has the design default of the primary hunting phenomenon, the improved design of the wheel-rail relationship has simply abandoned the high-quality technical resources of wheel-rail matching conditions at low conicity. On the contrary, the dynamic simulation analyses of MC01-TC02-MC03 three-vehicles trainset show that the semiactive damping technique between intervehicles takes advantage of Izz >> Ixx to improve the impacts of car body instability on ride comfort, and the self-adaptive improved design has consequently the ability to achieve the technical goal of uniform wear at low conicity. On the premise of meeting the requirements of crossing over different speed grade dedicated lines and realizing the running operations on three-speed levels of 160/250/350 km/h, the self-adaptive higher-/high-speed bogies can conditionally satisfy the economic reprofiling requirements of wheelsets through the optimal routing planning.

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İnan, G., A. B. Göktepe, K. Ramyar et A. Sezer. « Prediction of sulfate expansion of PC mortar using adaptive neuro-fuzzy methodology ». Building and Environment 42, n^o 3 (mars 2007) : 1264–69. http://dx.doi.org/10.1016/j.buildenv.2005.11.029.

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Schweiker, Marcel, Sabine Brasche, Wolfgang Bischof, Maren Hawighorst, Karsten Voss et Andreas Wagner. « Development and validation of a methodology to challenge the adaptive comfort model ». Building and Environment 49 (mars 2012) : 336–47. http://dx.doi.org/10.1016/j.buildenv.2011.08.002.

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Кійко, С. Г. « Predictive adaptation methodology for portfolio management of energy saving projects at metallurgical enterprises ». Системи обробки інформації, n^o 3(162), (30 septembre 2020) : 52–64. http://dx.doi.org/10.30748/soi.2020.162.06.

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A methodology for managing portfolios of energy saving projects at metallurgical enterprises is proposed. It forms a paradigm of predictive adaptation based on interconnected adaptive systems for planning, monitoring and managing changes and allows for forecasting energy consumption for complex technological processes and production, as well as modeling and evaluating the quality of the fuel and energy balance, in conditions of limited resources and risks, to form and select energy saving projects for implementation, while coordinating the priorities of the business strategy and the energy efficiency strategy of the metallurgical enterprise. A multi-level model of energy consumption of a metallurgical enterprise has been developed, which makes it possible to assess the effectiveness of energy-saving projects selected for implementation, objectively assess the share of each energy resource in the total flow, determine the energy intensity of a separate production, workshop, and the entire enterprise, and adjust the strategic direction in energy management. Using the model, it is possible to solve a number of tasks, including assessing the rationality and efficiency of the existing energy consumption structure at the enterprise, predicting the expected levels of energy consumption when changing the technology, product range and quality, and comparing various technologies and equipment in terms of energy efficiency, optimal management of energy flows taking into account changes in production conditions. The basic requirements for the organization of a planning and management system for a portfolio of energy saving projects at a metallurgical enterprise are formulated. The block diagram of a computer system for planning and managing a portfolio of energy saving projects at PJSC "Dneprospetsstal" is presented. The developed system of energy saving processes should be built into the system of enterprise processes, correspond to the strategic goals of the enterprise and the characteristics of the production process. The scheme of energy costs planning process implemented at the enterprise was considered.

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Samaniego, Franklin, Javier Sanchis, Sergio García-Nieto et Raúl Simarro. « Recursive Rewarding Modified Adaptive Cell Decomposition (RR-MACD) : A Dynamic Path Planning Algorithm for UAVs ». Electronics 8, n^o 3 (8 mars 2019) : 306. http://dx.doi.org/10.3390/electronics8030306.

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A relevant task in unmanned aerial vehicles (UAV) flight is path planning in 3 D environments. This task must be completed using the least possible computing time. The aim of this article is to combine methodologies to optimise the task in time and offer a complete 3 D trajectory. The flight environment will be considered as a 3 D adaptive discrete mesh, where grids are created with minimal refinement in the search for collision-free spaces. The proposed path planning algorithm for UAV saves computational time and memory resources compared with classical techniques. With the construction of the discrete meshing, a cost response methodology is applied as a discrete deterministic finite automaton (DDFA). A set of optimal partial responses, calculated recursively, indicates the collision-free spaces in the final path for the UAV flight.

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Jiahua, Pan, Zheng Yan et Anil Markandya. « Enfoques de adaptación al cambio climático en China : Un marco operativo ». Economía Agraria y Recursos Naturales 11, n^o 1 (31 octobre 2011) : 99. http://dx.doi.org/10.7201/earn.2011.01.05.

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<div>Climate change poses great risks for China, which makes adaptation an essential response. However, adaptation planning and implementation are still at a preliminary stage with respect to the theoretical framework and methodology. This article focuses on the status, problems and basic needs as regards adaptation to climate change, and outlines the operational framework that the government is seeking to pursue for China’s adapting to climate change. The conclusion is that, to satisfy the basic needs of development, it is necessary to clarify development-oriented and incremental adaptation. Furthermore measures to enhance adaptive capacity can be classified as infrastructure-based, technology-based and institutional. Lastly the authors stress the importance of appraising adaptation actions and measures from an economic perspective.</div>

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Ponis, Stavros T., Angelos Delis, Sotiris P. Gayialis, Panagiotis Kasimatis et Joseph Tan. « Applying Discrete Event Simulation (DES) in Healthcare ». International Journal of Healthcare Information Systems and Informatics 8, n^o 3 (juillet 2013) : 58–79. http://dx.doi.org/10.4018/jhisi.2013070104.

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This paper highlights the opportunities and challenges of applying Discrete Event Simulation (DES) to support capacity planning of a network of outpatient facilities. Despite an abundance of studies using simulation techniques to examine the operation and performance of outpatient clinics, the problem of capacity allocation and planning of medical services within a network of outpatient healthcare facilities appears to be underexplored. Here, a case study of a health insurance provider that operates a network of six outpatient medical facilities in the US is used to illustrate and explore the synthesizing and adaptive, yet parsimonious nature of using DES methodology for network design and capacity planning. Results of this case study demonstrate that significant performance improvements for the network operator can be achieved with applying DES method to support the network facility capacity planning process.

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Meng, Yiping, Yiming Sun et Wen-shao Chang. « Optimal trajectory planning of complicated robotic timber joints based on particle swarm optimization and an adaptive genetic algorithm ». Construction Robotics 5, n^o 2 (11 avril 2021) : 131–46. http://dx.doi.org/10.1007/s41693-021-00057-w.

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AbstractIn this paper, a methodology for path distance and time synthetic optimal trajectory planning is described in order to improve the work efficiency of a robotic chainsaw when dealing with cutting complex timber joints. To demonstrate this approach one specific complicated timber joint is used as an example. The trajectory is interpolated in the joint space by using a quantic polynomial function which enables the trajectory to be constrained in the kinematic limits of velocity, acceleration, and jerk. The particle swarm optimization (PSO) is applied to optimize the path of all cutting surfaces of the timber joint in operating space to achieve the shortest path. Based on the optimal path, an adaptive genetic algorithm (AGA) is used to optimize the time interval of interpolation points of every joint to realize the time-optimal trajectory. The results of the simulation show that the PSO method shortens the distance of the trajectory and that the AGA algorithm reduces time intervals and helps to obtain smooth trajectories, validating the effectiveness and practicability of the two proposed methodology on path and time optimization for 6-DOF robots when used in cutting tasks.

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Kumar, Priyadarshi Biplab, Dayal R. Parhi et Chinmaya Sahu. « An approach to optimize the path of humanoid robots using a hybridized regression-adaptive particle swarm optimization-adaptive ant colony optimization method ». Industrial Robot : the international journal of robotics research and application 46, n^o 1 (21 janvier 2019) : 104–17. http://dx.doi.org/10.1108/ir-10-2018-0204.

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PurposeWith enhanced use of humanoids in demanding sectors of industrial automation and smart manufacturing, navigation and path planning of humanoid forms have become the centre of attraction for robotics practitioners. This paper aims to focus on the development and implementation of a hybrid intelligent methodology to generate an optimal path for humanoid robots using regression analysis, adaptive particle swarm optimization and adaptive ant colony optimization techniques.Design/methodology/approachSensory information regarding obstacle distances are fed to the regression controller, and an interim turning angle is obtained as the initial output. Adaptive particle swarm optimization technique is used to tune the governing parameter of adaptive ant colony optimization technique. The final output is generated by using the initial output of regression controller and tuned parameter from adaptive particle swarm optimization as inputs to the adaptive ant colony optimization technique along with other regular inputs. The final turning angle calculated from the hybrid controller is subsequently used by the humanoids to negotiate with obstacles present in the environment.FindingsAs the current investigation deals with the navigational analysis of single as well as multiple humanoids, a Petri-Net model has been combined with the proposed hybrid controller to avoid inter-collision that may happen in navigation of multiple humanoids. The hybridized controller is tested in simulation and experimental platforms with comparison of navigational parameters. The results obtained from both the platforms are found to be in coherence with each other. Finally, an assessment of the current technique with other existing navigational model reveals a performance improvement.Research limitations/implicationsThe proposed hybrid controller provides satisfactory results for navigational analysis of single as well as multiple humanoids. However, the developed hybrid scheme can also be attempted with use of other smart algorithms.Practical implicationsHumanoid navigation is the present talk of the town, as its use is widespread to multiple sectors such as industrial automation, medical assistance, manufacturing sectors and entertainment. It can also be used in space and defence applications.Social implicationsThis approach towards path planning can be very much helpful for navigating multiple forms of humanoids to assist in daily life needs of older adults and can also be a friendly tool for children.Originality/valueHumanoid navigation has always been tricky and challenging. In the current work, a novel hybrid methodology of navigational analysis has been proposed for single and multiple humanoid robots, which is rarely reported in the existing literature. The developed navigational plan is verified through testing in simulation and experimental platforms. The results obtained from both the platforms are assessed against each other in terms of selected navigational parameters with observation of minimal error limits and close agreement. Finally, the proposed hybrid scheme is also evaluated against other existing navigational models, and significant performance improvements have been observed.

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Jia, Zhiwei, Haohui Liu, Haoliang Zheng, Shaosheng Fan et Zheng Liu. « An Intelligent Inspection Robot for Underground Cable Trenches Based on Adaptive 2D-SLAM ». Machines 10, n^o 11 (1 novembre 2022) : 1011. http://dx.doi.org/10.3390/machines10111011.

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With the rapid growth of underground cable trenches, the corresponding inspections become a heavy burden, and an intelligent inspection robot for automatic examinations in underground cable trenches would be a suitable solution. To achieve this, this paper establishes one new navigation methodology for intelligent inspection robots, especially when applied in complex scenarios and the corresponding hardware. Firstly, to map the underground trenches with higher precision, an improved graph optimization cartographer-SLAM algorithm is proposed, which is based on the combination of depth camera and LIDAR. The depth image is converted into pseudo laser data, and fused with LIDAR data for calibration. Secondly, to overcome the low precision of the Laser odometer due to the uneven ground, an adaptive keyframe selection method is designed. Thirdly, the forward A* model is presented, which has been adjusted in three aspects, including the convergence of node searching, the cost function, and the path smoothness, to adapt to the narrow underground environment for global path planning. Fourthly, to realize dynamic obstacle avoidance, an improved fusion scheme is built to integrate the proposed global path planning algorithm and the dynamic window approach (DWA). In the case study, the simulation experiments showed the advantage of the forward A* algorithm over the state-of-the-art algorithm in both time consumption and the number of inflection points generated, the field tests illustrated the effect of the fusion of depth camera images and LIDAR. Hence, the feasibility of this navigation methodology can be verified, and the average length of path and time consumption decreased by 6.5% and 17.8%, respectively, compared with the traditional methods.

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Xu, Bu Quan, Li Chen Zhang et Bu Zhen Xu. « Cloud Adapt Particle Swarm Optimization Algorithm for Distribution Network Planning with Distributed Generation ». Applied Mechanics and Materials 427-429 (septembre 2013) : 1136–40. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.1136.

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Distributed Generation (DG) can be used to improve power quality, power supply reliability and reduce network loss et. Meanwhile Particle Swarm Optimization algorithm (PSO) is easy to fall into the local minimum. In this paper we propose a Cloud Adaptive Particle Swarm Optimization algorithm (CAPSO) to optimize the site and size of DG based on cloud model which has a tendency and randomness property. Judged by two dynamic value assessment, particle belongs to which group, excellent, general and poor. The inertia weight in general group is adaptively varied depending on X-conditional cloud generation. Taking the minimum network loss as the objective function, simulation on the IEEE 33BUS distribution systems to validate the methodology. Analysis and simulations indicate that it has good convergence speed and exactness.

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Carmichael, Bethune, Greg Wilson, Ivan Namarnyilk, Sean Nadji, Jacqueline Cahill, Sally Brockwell, Bob Webb, Deanne Bird et Cathy Daly. « A Methodology for the Assessment of Climate Change Adaptation Options for Cultural Heritage Sites ». Climate 8, n^o 8 (24 juillet 2020) : 88. http://dx.doi.org/10.3390/cli8080088.

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Cultural sites are particularly important to Indigenous peoples, their identity, cosmology and sociopolitical traditions. The benefits of local control, and a lack of professional resources, necessitate the development of planning tools that support independent Indigenous cultural site adaptation. We devised and tested a methodology for non-heritage professionals to analyse options that address site loss, build site resilience and build local adaptive capacity. Indigenous rangers from Kakadu National Park and the Djelk Indigenous Protected Area, Arnhem Land, Australia, were engaged as fellow researchers via a participatory action research methodology. Rangers rejected coastal defences and relocating sites, instead prioritising routine use of a risk field survey, documentation of vulnerable sites using new digital technologies and widely communicating the climate change vulnerability of sites via a video documentary. Results support the view that rigorous approaches to cultural site adaptation can be employed independently by local Indigenous stakeholders.

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Wang, Jianhua, Jianrong Dai, Yongjie Jing, Yanan Huo et Tianye Niu. « Methodology for Registration of Shrinkage Tumors in Head-and-Neck CT Studies ». Computational and Mathematical Methods in Medicine 2015 (2015) : 1–9. http://dx.doi.org/10.1155/2015/265497.

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Tumor shrinkage occurs in many patients undergoing radiotherapy for head-and-neck (H&N) cancer. However, one-to-one correspondence is not always available between voxels of two image sets. This makes intensity-based deformable registration difficult and inaccurate. In this paper, we describe a novel method to increase the performance of the registration in presence of tumor shrinkage. The method combines an image modification procedure and a fast symmetric Demons algorithm to register CT images acquired at planning and posttreatment fractions. The image modification procedure modifies the image intensities of the primary tumor by calculating tumor cell survival rate using the linear quadratic (LQ) model according to the dose delivered to the tumor. A scale operation is used to deal with uncertainties in biological parameters. The method was tested in 10 patients with nasopharyngeal cancer (NPC). Registration accuracy was improved compared with that achieved using the symmetric Demons algorithm. The average Dice similarity coefficient (DSC) increased by 21%. This novel method is suitable for H&N adaptive radiation therapy.

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Tang, Biwei, Zhu Zhanxia et Jianjun Luo. « A convergence-guaranteed particle swarm optimization method for mobile robot global path planning ». Assembly Automation 37, n^o 1 (6 février 2017) : 114–29. http://dx.doi.org/10.1108/aa-03-2016-024.

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Purpose Aiming at obtaining a high-quality global path for a mobile robot which works in complex environments, a modified particle swarm optimization (PSO) algorithm, named random-disturbance self-adaptive particle swarm optimization (RDSAPSO), is proposed in this paper. Design/methodology/approach A perturbed global updating mechanism is introduced to the global best position to avoid stagnation in RDSAPSO. Moreover, a new self-adaptive strategy is proposed to fine-tune the three control parameters in RDSAPSO to dynamically adjust the exploration and exploitation capabilities of RDSAPSO. Because the convergence of PSO is paramount and influences the quality of the generated path, this paper also analytically investigates the convergence of RDSAPSO and provides a convergence-guaranteed parameter selection principle for RDSAPSO. Finally, a RDSAPSO-based global path planning (GPP) method is developed, in which the feasibility-based rule is applied to handle the constraint of the problem. Findings In an attempt to validate the proposed method, it is compared against six state-of-the-art evolutionary methods under three different numerical simulations. The simulation results confirm that the proposed method is highly competitive in terms of the path optimality. Moreover, the computation time of the proposed method is comparable with those of the other compared methods. Originality/value Therefore, the proposed method can be considered as a vital alternative in the field of GPP.

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Zhang, Wenguang, Xiaoyu Guan, Xueqin Zhou et Ji Lu. « The effect of career adaptability on career planning in reaction to automation technology ». Career Development International 24, n^o 6 (3 octobre 2019) : 545–59. http://dx.doi.org/10.1108/cdi-05-2018-0135.

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Purpose This study investigated employees’ career planning in preparation for the impact of manufacturing transformation triggered by automation technology. Built on career construction theory, the purpose of this paper is to conceptualize career planning as an attempt to integrate oneself into the social environment. In this process of integration, career adaptability is a critical psychological resource for adaptation to anticipated changes. Design/methodology/approach Through an online survey, 476 participants answered questions regarding the following aspects: perceptions of the threats and opportunities posed by automation technology; career adaptability, that is, career-related concern, control, curiosity, and confidence in adapting to occupational transitions; and career plans and actions to address the challenge, including short-term job crafting behaviors and long-term career adjustment plan. Findings The results showed that opportunity and threat perceptions were associated with one’s job crafting behavior and long-term career adjustment plan and such relationships were moderated by career adaptability and work experience relevant to automation technologies. Specifically, career adaptability is a psychological resource helping individuals deal with perceived challenges, while relevant work experience moderated one’s strategies to catch opportunities. Originality/value This study contributes to the understanding of psychosocial determinants for better career planning in the midst of the industrial revolution. Policies that aim to prepare workers for the upcoming social transition may benefit from this study to leverage adaptive and proactive behaviors at a societal level.

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Bochkov, Pavel. « CORRECTIVE STRATEGY AND TACTICS OF OVERCOMING IMPAIRED BALANCE IN PRESCHOOLERS. » Scientific journal of Khortytsia National Academy, n^o 2 (2020) : 155–63. http://dx.doi.org/10.51706/2707-3076-2020-2-16.

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The article reveals the system features of planning corrective measures for the formation of the balance function of preschool children with musculoskeletal system disorders. The innovative planning concept implies a harmonious combination of a correction strategy, that should be responsible for the long-term vector of achieving the desired target result, with the corrective tactics of overcoming specific children’s disorders. The strategy reflects a constant component of the correction process and is relatively unchanged, whereas the corrective tactic is based on the variability of individual planning, followed by appropriate methodological support for the implementation of this program for a particular child. The author analyzes the existing approaches in the planning physical education and physical rehabilitation. The analysis revealed the insufficient methodological foundations for the planning of corrective measures to improve the balance function in preschool children with musculoskeletal system disorders. The general principles of planning adaptive physical education for preschool children with musculoskeletal system disorders are considered. The general planning principles (phylogenetic principle, age, calendar, intra-cycle, repetition, the principle of "steps") of adaptive physical education for preschool children with musculoskeletal system disorders were revealed, they were proposed in the technique of N.Efimenko and P.Bochkov. On this basis, a methodology for the phased planning of the targeted formation of the equilibrium function was developed, which reflects the logic of stimulating the five channels of the postural aplomb system and takes into account the peculiarities of postural deficiency in each case. In the conclusions the algorithm of the system for planning correctivee measures to improve the balance function in this category of children is presented. The prospects for research of effective ways of overcoming the postural deficiency in children with musculoskeletal disorders is outlined.

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Zukowski, Rebecca S. « The Impact of Adaptive Capacity on Disaster Response and Recovery : Evidence Supporting Core Community Capabilities ». Prehospital and Disaster Medicine 29, n^o 4 (1 juillet 2014) : 380–87. http://dx.doi.org/10.1017/s1049023x14000624.

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AbstractIntroductionThe aim of this study was to determine if a relationship exists between the development of adaptive capacity and disaster response and recovery outcomes. Hospitals and health care systems are a critical element in community planning for all phases of the disaster cycle. There is a lack of research, however, to validate the relationship between the development of these capabilities and improved response and recovery outcomes.Hypothesis/ProblemTwo hypotheses were formulated to address the research question. The first hypothesis argued that counties or parishes that developed adaptive capacity through pre-event planning, community engagement, training, and the use of national response frameworks would have improved response and recovery performance outcomes. The second hypothesis argued that adaptive capacity, along with response and recovery performance outcomes, predicts the trajectory of recovery progression.MethodsThis study employed a quantitative cross-sectional survey methodology and existing community demographic data to explore the development of adaptive capacity and its ability to predict disaster response and recovery outcomes in communities affected by major disaster in 2011. A total of 333 counties and parishes were included in the final sample, providing a 95% confidence interval with a 5% margin of error. Data were analyzed using both descriptive and inferential statistics. Multiple, hierarchical, and robust regression were used to find the best fitting model. Multi-level modeling with random intercepts was used to control for the nesting effects associated with county, state, and the Federal Emergency Management Agency (FEMA) region sampling.ResultsDescriptive results provide a baseline assessment of adaptive capacity development at the community level. While controlling for other variables, hypothesis testing revealed that pre-event planning, community engagement, full-scale exercises, and use of national frameworks predicated overall response and recovery performance outcomes (R2 = .43; F13,303 = 13.34; P < .001). In terms of recovery progression, pre-event planning, overall response and recovery performance outcome, total time of disruption, and percent of people below poverty were significant (R2 = .15; F14,302 = 4.53; P < .001).ConclusionsEstablishment of empirical data provides communities with reinforcement to continue resilience-building activities at the local level. However, findings from this study suggest that only full-scale exercises were significant in improving response and recovery outcomes. Implications for re-evaluation of disaster training warrant further exploration.ZukowskiRS. The impact of adaptive capacity on disaster response and recovery: evidence supporting core community capabilities. Prehosp Disaster Med. 2014;29(4):1-8.

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McKee, Jacob J., Amy N. Rose, Edward A. Bright, Timmy Huynh et Budhendra L. Bhaduri. « Locally adaptive, spatially explicit projection of US population for 2030 and 2050 ». Proceedings of the National Academy of Sciences 112, n^o 5 (20 janvier 2015) : 1344–49. http://dx.doi.org/10.1073/pnas.1405713112.

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Localized adverse events, including natural hazards, epidemiological events, and human conflict, underscore the criticality of quantifying and mapping current population. Building on the spatial interpolation technique previously developed for high-resolution population distribution data (LandScan Global and LandScan USA), we have constructed an empirically informed spatial distribution of projected population of the contiguous United States for 2030 and 2050, depicting one of many possible population futures. Whereas most current large-scale, spatially explicit population projections typically rely on a population gravity model to determine areas of future growth, our projection model departs from these by accounting for multiple components that affect population distribution. Modeled variables, which included land cover, slope, distances to larger cities, and a moving average of current population, were locally adaptive and geographically varying. The resulting weighted surface was used to determine which areas had the greatest likelihood for future population change. Population projections of county level numbers were developed using a modified version of the US Census’s projection methodology, with the US Census’s official projection as the benchmark. Applications of our model include incorporating multiple various scenario-driven events to produce a range of spatially explicit population futures for suitability modeling, service area planning for governmental agencies, consequence assessment, mitigation planning and implementation, and assessment of spatially vulnerable populations.

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Johnson, Bonnie J. « Planners as leaders : finding their comfort zone ». International Journal of Public Leadership 14, n^o 3 (13 août 2018) : 155–78. http://dx.doi.org/10.1108/ijpl-04-2018-0022.

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Purpose Planners are expected to leave leadership to elected officials. Yet, they are often asked to do more. Should planners lead? The purpose of this paper is to examine how leadership is seen in the profession and then outline major theories of leadership and planning. Design/methodology/approach Using content analysis, the major theories of planning and descriptions of what planners do from professional planning organizations’ codes of ethics from around the world are compared. Findings Results indicate that new ways of thinking about leadership (Group leadership, Servant, Adaptive, Authentic and Followership) can help planners find leadership styles that fit their comfort zones better than old leadership definitions emphasizing heroic individuals. Originality/value Existing literature regarding leadership in planning indicates that planners must run for office if they are to lead. This examination of planners’ codes of ethics and newer theories of leadership indicates they can be leaders and operate well within current ethical boundaries.

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Pandey, Krishna Kant, Chandrashekhar Kumbhar, Dayal R. Parhi, Sandeep Kumar Mathivanan, Prabhu Jayagopal et Aminul Haque. « Trajectory Planning and Collision Control of a Mobile Robot : A Penalty-Based PSO Approach ». Mathematical Problems in Engineering 2023 (31 janvier 2023) : 1–10. http://dx.doi.org/10.1155/2023/1040461.

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In this paper, trajectory planning and navigation control problems have been addressed for a mobile robot. To achieve the objective of the research, an adaptive PSO (Particle Swarm Optimization) motion algorithm is developed using a penalty-based methodology. To deliver the best or collision-free position to the robot, fitness values of the all-random-positioned particles are compared at the same time during the target search action. By comparing the fitness values, the robot occupies the best position in the search space till it reaches the target. The new work integrated with conventional PSO is varying a velocity event that plays a vital role during the position acquisition (continuous change in position during the obstacle negotiation with the communication through random-positioned particles). The obstacle-negotiating angle and positional velocity of the robot are considered as input parameters of the controller whereas the robot's best position according to the target position is considered as the output of the controller. Simulation results are presented through the MATLAB environment. To validate simulation results, real-time experiments have been conducted in a similar workspace. The results of the adaptive PSO technique are also compared with the results of the existing navigational techniques. Improvements in results between the proposed navigation technique and existing navigation techniques are found to be 4.66% and 11.30%, respectively.

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Chari, Martin Munashe, Hamisai Hamandawana et Leocadia Zhou. « Using geostatistical techniques to map adaptive capacities of resource-poor communities to climate change ». International Journal of Climate Change Strategies and Management 10, n^o 5 (19 novembre 2018) : 670–88. http://dx.doi.org/10.1108/ijccsm-03-2017-0071.

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Purpose This paper aims to present a case study-based approach to identify resource-poor communities with limited abilities to cope with the adverse effects of climate change. The study area is the Nkonkobe Local Municipality, in the Eastern Cape which is one of South Africa’s provinces ranked as being extremely vulnerable to the adverse effects of climate change because of high incidences of poverty and limited access to public services such as water and education. Although adaptive capacity and vulnerability assessments help to guide policy formulation and implementation by identifying communities with low coping capacities, policy implementers often find it difficult to fully exploit the utility of these assessments because of difficulties in identifying vulnerable communities. The paper attempts to bridge this gap by providing a user-friendly, replicable, practically implementable and adaptable methodology that can be used to cost-effectively and timeously identify vulnerable communities with low coping capacities. Design/methodology/approach A geostatistical approach was used to assess and evaluate adaptive capacities of resource-poor communities in the Nkonkobe Local Municipality. The geospatial component of this approach consisted of a multi-step Geographical Information Systems (GIS) based technique that was improvised to map adaptive capacities of different communities. The statistical component used demographic indicators comprising literacy levels, income levels, population age profiles and access to water to run automated summation and ranking of indicator scores in ArcGIS 10.2 to produce maps that show spatial locations of communities with varying levels of adaptive capacities on a scale ranging from low, medium to high. Findings The analysis identified 14 villages with low adaptive capacities from a total of 180 villages in the Nkonkobe Local Municipality. This finding is important because it suggests that our methodology can be effectively used to objectively identify communities that are vulnerable to climate change. Social implications The paper presents a tool that could be used for targeting assistance to climate change vulnerable communities. The methodology proposed is of general applicability in guiding public policy interventions aimed at reaching, protecting and uplifting socio-economically disadvantaged populations in both rural and urban settings. Originality/value The approach’s ability to identify vulnerable communities is useful because it aids the identification of resource-poor communities that deserve priority consideration when planning adaptation action plans to deliver support and assistance to those least capable of effectively coping with the adverse effects of climate change induced vulnerabilities.

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