Journal articles: 'Searching behavior – Mathematical models'

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Altowayti, Wahid Ali Hamood, Norzila Othman, Husnul Azan Tajarudin, Arafat Al-Dhaqm, Syazwani Mohd Asharuddin, Adel Al-Gheethi, Abdullah Faisal Alshalif, et al. "Evaluating the Pressure and Loss Behavior in Water Pipes Using Smart Mathematical Modelling." Water 13, no. 24 (December 8, 2021): 3500. http://dx.doi.org/10.3390/w13243500.

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Due to the constant need to enhance water supply sources, water operators are searching for solutions to maintain water quality through leakage protection. The capability to monitor the day-to-day water supply management is one of the most significant operational challenges for water companies. These companies are looking for ways to predict how to improve their supply operations in order to remain competitive, given the rising demand. This work focuses on the mathematical modeling of water flow and losses through leak openings in the smart pipe system. The research introduces smart mathematical models that water companies may use to predict water flow, losses, and performance, thereby allowing issues and challenges to be effectively managed. So far, most of the modeling work in water operations has been based on empirical data rather than mathematically described process relationships, which is addressed in this study. Moreover, partial submersion had a power relationship, but a total immersion was more likely to have a linear power relationship. It was discovered in the experiment that the laminar flows had Reynolds numbers smaller than 2000. However, when testing with transitional flows, Reynolds numbers were in the range of 2000 to 4000. Furthermore, tests with turbulent flow revealed that the Reynolds number was more than 4000. Consequently, the main loss in a 30 mm diameter pipe was 0.25 m, whereas it was 0.01 m in a 20 mm diameter pipe. However, the fitting pipe had a minor loss of 0.005 m, whereas the bending pipe had a loss of 0.015 m. Consequently, mathematical models are required to describe, forecast, and regulate the complex relationships between water flow and losses, which is a concept that water supply companies are familiar with. Therefore, these models can assist in designing and operating water processes, allowing for improved day-to-day performance management.

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Luo, Shuren. "An Empirical Study on the Impact Mechanism of Big Data-based Precision Push Models on Consumers’ Online Buying Behavior in Southwest District of China." Learning & Education 10, no. 3 (November 7, 2021): 251. http://dx.doi.org/10.18282/l-e.v10i3.2476.

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In the era of big data, consumers, as the main body of the economy, had been affected to a large extent by purchasing behavior. This impact would have mainly been reflected in the changes in consumer behavior, coupled with the development of the e-commerce industry in society. Consumers did change from traditional physical store purchases to online purchases as consumers’ online purchases increased. However, in the face of many commodities, it would be difficult for users to find items of interest. The precision push model came into being the user’s mathematical modeling based on the user’s behavior characteristics for searching the user’s possible feelings in items of interest to users. However, whether the matching of the precise push mode and the user interacted effectively, promoting and stimulating the consumption behavior of consumers would still face the problem of accuracy and efficiency.

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Ilyina, Elena A., and Leonid A. Saraev. "On the theory of optimization of transaction costs of multifactor manufacturing enterprises." Vestnik of Samara University. Economics and Management 12, no. 4 (December 30, 2021): 182–94. http://dx.doi.org/10.18287/2542-0461-2021-12-4-182-194.

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The published article proposes mathematical models for calculating the optimal profit of multifactorial manufacturing enterprises that incur both production (transformational) and certain non-production (transactional) costs, the sources of which may be forced costs of searching for economic information, measuring the parameters of various goods, negotiating and the conclusion of contracts, for the development of specifications and the protection of property rights, for the opportunistic behavior of employees and managers of the enterprise, etc. Anumerical analysis of the presented models for calculating the optimal profit of multifactor enterprises that bear transaction costs shows the unattainability of the maximum possible profit values, since in practice the enterprise management maximizes not the profit itself, but its utility, expressed in the form of the corresponding transaction function.

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Chai Lian, Oh, Choong Kok Keong, Toku Nishimura, and Kim Jae-Yeol. "Form-Finding of Spine Inspired Biotensegrity Model." Applied Sciences 10, no. 18 (September 11, 2020): 6344. http://dx.doi.org/10.3390/app10186344.

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This paper presents a study on form-finding of four-stage class one self-equilibrated spine biotensegrity models. Advantageous features such as slenderness and natural curvature of the human spine, as well as the stabilizing network that consists of the spinal column and muscles, were modeled and incorporated in the mathematical formulation of the spine biotensegrity models. Form-finding analysis, which involved determination of independent self-equilibrium stress modes using generalized inverse and their linear combination, was carried out. Form-finding strategy for searching the self-equilibrated models was studied through two approaches: application of various combinations of (1) twist angles and (2) nodal coordinates. A total of three configurations of the spine biotensegrity models with different sizes of triangular cell were successfully established for the first time in this study. All members in the spine biotensegrity models satisfied the assumption of linear elastic material behavior. With the established spine biotensegrity model, the advantageous characteristics of flexibility and versatility of movement can be further studied for potential application in deployable structures and flexible arm in the robotic industry.

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Hills, Daniel J. A., Adrian M. Grütter, and Jonathan J. Hudson. "An algorithm for discovering Lagrangians automatically from data." PeerJ Computer Science 1 (November 4, 2015): e31. http://dx.doi.org/10.7717/peerj-cs.31.

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An activity fundamental to science is building mathematical models. These models are used to both predict the results of future experiments and gain insight into the structure of the system under study. We present an algorithm that automates the model building process in a scientifically principled way. The algorithm can take observed trajectories from a wide variety of mechanical systems and, without any other prior knowledge or tuning of parameters, predict the future evolution of the system. It does this by applying the principle of least action and searching for the simplest Lagrangian that describes the system’s behaviour. By generating this Lagrangian in a human interpretable form, it can also provide insight into the workings of the system.

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Andrey Mastislavovich, Korneev, Buzina Olga Petrovna, Sukhanov Andrey Vladimirovich, and Shipulin Ilya Andreevich. "Experience in Using Stochastic Optimization Methods for Determining Numerical Parameters of Models in Materials Structurization Management Systems." International Journal of Engineering & Technology 7, no. 3.5 (July 7, 2018): 32. http://dx.doi.org/10.14419/ijet.v7i3.5.15196.

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The task of intellectual support of the process of composition formation for materials with a composite structure occurs when designing and operating automated control systems for multi-stage production processes. Such automated systems function in direct interaction with the external environment, and should promptly return the results of processing to the environment in the form of corrective actions or as messages to the user. The need for correct and complete mathematical models and fast, accurate algorithms that solve multistage problems often arises when structuring composite materials. In this case, mathematical models contain sets of numerical parameters and the search for exact values for them presents a complex optimization problem. The purpose of this paper is to investigate the possibility of using stochastic optimization methods to determine the exact numerical values of the calculated parameters of mathematical models that mimic the behavior of a structured composite material with given physico-mechanical characteristics under operating conditions. To carry out the research, special software has been created that implements algorithms for searching for extreme values for functions of several variables. The functional purpose of the software is intellectual support for decision-making in the formation of chemical compositions of cast iron alloys. Another developed system is designed to make effective decisions when designing the composition and structure of composite materials containing discrete fibers. Optimization of the calculated parameters was performed on a definite and fixed search area, which is a hyperparallelepiped. The program implements ten modifications of the simulation algorithm for annealing, allowing for a finite number of steps to make an estimate of the optimal value of the input elements of the function under study on a multidimensional space. In particular, modification of A, B and B algorithm schemes using the Boltzmann and Cauchy distribution functions, as well as the superfast annealing algorithm and the Xin Yao algorithm are implemented. The obtained data allowed to draw conclusions about the advantages and disadvantages of each modification of the stochastic search algorithm..

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Carreira, Pedro, Nuno Alves, Carina Ramos, and Paulo J. Bártolo. "Bio Inspired Algorithms for Injection Moulding Optimization." Advanced Materials Research 683 (April 2013): 771–74. http://dx.doi.org/10.4028/www.scientific.net/amr.683.771.

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Social behaviors of living organisms found in nature, like food searching, environment fitness and survival are inspiration for meta-heuristic mathematical models. Replicating these natural organism behaviors, several optimization algorithms have been developed and applied to technological processes. In this work, some nature inspired algorithms are applied to the injection problem in order to optimize the injection runners’ geometry, so that the overall cycle time is minimized. A key issue is the injection moulding process, as it strongly determines the cost per part. A global optimization strategy was implemented for the injection moulding cycle time, covering the main steps of process, filling time, cooling time, packing time and opening time. To achieve the optimum solution for each design variable and obtain the best time solution overall, it will enable to evaluate optimality, robustness, convergence, and variables dispersion for each used algorithm.

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Mokshin, Anatolii V., Vladimir V. Mokshin, and Diana A. Mirziyarova. "Formation of Regression Model for Analysis of Complex Systems Using Methodology of Genetic Algorithms." Nonlinear Phenomena in Complex Systems 23, no. 3 (October 28, 2020): 317–26. http://dx.doi.org/10.33581/1561-4085-2020-23-3-317-326.

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This study presents the approach to analyze evolution of an arbitrary complex system whose behavior is characterized by a set of different time-dependent factors. The key requirement for these factors is that they must contain an information about the system only; it does not matter at all what the nature (physical, biological, social, economic, etc.) of a complex system is. Within the framework of the presented theoretical approach, the problem of searching for non-linear regression models that express the relationship between these factors for a complex system under study is solved. It will be shown that this problem can be solved using the methodology of genetic (evolutionary) algorithms. The resulting regression models make it possible to predict the most probable evolution of the considered system, as well as to determine the significance of some factors and, thereby, to formulate some recommendations to drive by this system. It will be shown that the presented theoretical approach can be used to analyze data (information) characterizing the educational process in the discipline"Physic" in the secondary school, and to develop the strategies for improving academic performance in this discipline.

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Campeau, Winston, Andrew M. Simons, and Brett Stevens. "The evolutionary maintenance of Lévy flight foraging." PLOS Computational Biology 18, no. 1 (January 18, 2022): e1009490. http://dx.doi.org/10.1371/journal.pcbi.1009490.

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Lévy flight is a type of random walk that characterizes the behaviour of many natural phenomena studied across a multiplicity of academic disciplines; within biology specifically, the behaviour of fish, birds, insects, mollusks, bacteria, plants, slime molds, t-cells, and human populations. The Lévy flight foraging hypothesis states that because Lévy flights can maximize an organism’s search efficiency, natural selection should result in Lévy-like behaviour. Empirical and theoretical research has provided ample evidence of Lévy walks in both extinct and extant species, and its efficiency across models with a diversity of resource distributions. However, no model has addressed the maintenance of Lévy flight foraging through evolutionary processes, and existing models lack ecological breadth. We use numerical simulations, including lineage-based models of evolution with a distribution of move lengths as a variable and heritable trait, to test the Lévy flight foraging hypothesis. We include biological and ecological contexts such as population size, searching costs, lifespan, resource distribution, speed, and consider both energy accumulated at the end of a lifespan and averaged over a lifespan. We demonstrate that selection often results in Lévy-like behaviour, although conditional; smaller populations, longer searches, and low searching costs increase the fitness of Lévy-like behaviour relative to Brownian behaviour. Interestingly, our results also evidence a bet-hedging strategy; Lévy-like behaviour reduces fitness variance, thus maximizing geometric mean fitness over multiple generations.

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Le Chau, Ngoc, Ngoc Thoai Tran, and Thanh-Phong Dao. "Behavior Analysis of a Flexure Hinge Array." Mathematical Problems in Engineering 2021 (April 13, 2021): 1–11. http://dx.doi.org/10.1155/2021/9947090.

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Compliant mechanisms have been well designed to reach an ultra-high accuracy in positioning systems. However, the displacement of compliant mechanisms is still a major problem that restricts practical applications. Hence, a new flexure hinge array (FHA) is proposed to improve its displacement in this article. This paper is aimed to design and optimize the FHA. The structure of FHA is constructed by series-parallel array. Analytical calculations of the FHA are derived so as to analyze the stiffness and deformation. The displacement of the FHA is optimized by moth-flame optimization algorithm. The results determined that optimal parameters are found at Lt1 of 20.58 mm, w t 1 of 1.92 mm, and w t 2 of 2.29 mm. Besides, the optimal displacement is about 27.02 mm. Through Kruskal–Wallis test, the results verified that the proposed MFO outperforms other optimization algorithms in terms of searching the largest displacement. Validations of the analytical models are verified through simulations and experiments. The theoretical results are close to the experimental results. Additionally, the displacement of the FHA is superior that of existing joints. The displacement in the z-direction is approximately 32 mm according to a displacement of 12 mm in the x-direction.

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Chen, Kai, Li Han, Shuhuan Wang, Junjie Lu, and Liping Shi. "Modified Antipredatory Particle Swarm Optimization for Dynamic Economic Dispatch with Wind Power." Mathematical Problems in Engineering 2019 (October 23, 2019): 1–17. http://dx.doi.org/10.1155/2019/5831362.

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A modified antipredatory particle swarm optimization (MAPSO) algorithm with evasive adjustment behavior is proposed to solve the dynamic economic dispatch problem of wind power. The algorithm adds the social avoidance inertia weight to the conventional antipredatory particle swarm optimization (APSO) speed update formula. The size of inertia weight is determined by the distance between the global worst particle and other particles. After normalizing the distance, the inertia weight is controlled within the ideal range by using the characteristics of sigmoid function and linear decreasing method, which improves the ability of particles to avoid the worst solution. Then, according to the characteristics of the acceleration coefficient which can adjust the local and global searching ability of particles, acceleration coefficients of nonlinear change strategy is proposed to improve the searching ability of the algorithm. Finally, the proposed algorithm is applied to several benchmark functions and power grid system models, and the results are compared with those reported using other algorithms, which prove the effectiveness and superiority of the proposed algorithm.

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Paneva-Marinova, Desislava. "A Semantic-Oriented Architecture of a Functional Module for Personalized and Adaptive Access to the Knowledge in a Multimedia Digital Library." Serdica Journal of Computing 2, no. 4 (February 16, 2009): 403–24. http://dx.doi.org/10.55630/sjc.2008.2.403-424.

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This paper presents dissertation work on semantic-oriented architectures and models for personalized and adaptive access to the knowledge in a multimedia digital library. The work was presented on October 27, 2008 before the Specialized Academic Council in Informatics and Mathematical Modelling at the Higher Attestation Commission. As a result of the work there appeared a functional module providing customized user access to the library content flow. The module used an IEEE PAPI and IMS LIP-oriented ontological user model. The main services provide customized user access, browsing, searching, and grouping of digitised objects and collections, user profile management, tracking the user’s behaviour, etc. The services require and trace out data about the preliminary level of the users’ knowledge in the domain covered by the digital library, their object observation style, cognitive goals and interests, preferences about the objects/collections presentation and grouping, physical limitations, used knowledge delivery channels (Web, mobile phone), etc. Then they transform the available digitised objects into a new personalized form, and finally deliver them to the user. The module uses special usage scenarios/instructions defining a wide range of service actions dependent on the user’s background, events, informal learning situations, knowledge delivery channels, etc.

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Tello, J. Ignacio, and Dariusz Wrzosek. "Predator–prey model with diffusion and indirect prey-taxis." Mathematical Models and Methods in Applied Sciences 26, no. 11 (October 2016): 2129–62. http://dx.doi.org/10.1142/s0218202516400108.

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We analyze predator–prey models in which the movement of predator searching for prey is the superposition of random dispersal and taxis directed toward the gradient of concentration of some chemical released by prey (e.g. pheromone), Model II, or released from damaged or injured prey due to predation (e.g. blood), Model I. The logistic O.D.E. describing the dynamics of prey population is coupled to a fully parabolic chemotaxis system describing the dispersion of chemoattractant and predator’s behavior. Global-in-time solutions are proved in any space dimension and stability of homogeneous steady states is shown by linearization for a range of parameters. For space dimension [Formula: see text] the basin of attraction of such a steady state is characterized by means of nonlinear analysis under some structural assumptions. In contrast to Model II, Model I possesses spatially inhomogeneous steady states at least in the case [Formula: see text].

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Kumar, Sreejan, Cameron T. Ellis, Thomas P. O’Connell, Marvin M. Chun, and Nicholas B. Turk-Browne. "Searching through functional space reveals distributed visual, auditory, and semantic coding in the human brain." PLOS Computational Biology 16, no. 12 (December 3, 2020): e1008457. http://dx.doi.org/10.1371/journal.pcbi.1008457.

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The extent to which brain functions are localized or distributed is a foundational question in neuroscience. In the human brain, common fMRI methods such as cluster correction, atlas parcellation, and anatomical searchlight are biased by design toward finding localized representations. Here we introduce the functional searchlight approach as an alternative to anatomical searchlight analysis, the most commonly used exploratory multivariate fMRI technique. Functional searchlight removes any anatomical bias by grouping voxels based only on functional similarity and ignoring anatomical proximity. We report evidence that visual and auditory features from deep neural networks and semantic features from a natural language processing model, as well as object representations, are more widely distributed across the brain than previously acknowledged and that functional searchlight can improve model-based similarity and decoding accuracy. This approach provides a new way to evaluate and constrain computational models with brain activity and pushes our understanding of human brain function further along the spectrum from strict modularity toward distributed representation.

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Gavrilescu, Marius, Sabina-Adriana Floria, Florin Leon, and Silvia Curteanu. "A Hybrid Competitive Evolutionary Neural Network Optimization Algorithm for a Regression Problem in Chemical Engineering." Mathematics 10, no. 19 (September 30, 2022): 3581. http://dx.doi.org/10.3390/math10193581.

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Neural networks have demonstrated their usefulness for solving complex regression problems in circumstances where alternative methods do not provide satisfactory results. Finding a good neural network model is a time-consuming task that involves searching through a complex multidimensional hyperparameter and weight space in order to find the values that provide optimal convergence. We propose a novel neural network optimizer that leverages the advantages of both an improved evolutionary competitive algorithm and gradient-based backpropagation. The method consists of a modified, hybrid variant of the Imperialist Competitive Algorithm (ICA). We analyze multiple strategies for initialization, assimilation, revolution, and competition, in order to find the combination of ICA steps that provides optimal convergence and enhance the algorithm by incorporating a backpropagation step in the ICA loop, which, together with a self-adaptive hyperparameter adjustment strategy, significantly improves on the original algorithm. The resulting hybrid method is used to optimize a neural network to solve a complex problem in the field of chemical engineering: the synthesis and swelling behavior of the semi- and interpenetrated multicomponent crosslinked structures of hydrogels, with the goal of predicting the yield in a crosslinked polymer and the swelling degree based on several reaction-related input parameters. We show that our approach has better performance than other biologically inspired optimization algorithms and generates regression models capable of making predictions that are better correlated with the desired outputs.

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Reddy, Gautam, Laura Desban, Hidenori Tanaka, Julian Roussel, Olivier Mirat, and Claire Wyart. "A lexical approach for identifying behavioural action sequences." PLOS Computational Biology 18, no. 1 (January 10, 2022): e1009672. http://dx.doi.org/10.1371/journal.pcbi.1009672.

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Animals display characteristic behavioural patterns when performing a task, such as the spiraling of a soaring bird or the surge-and-cast of a male moth searching for a female. Identifying such recurring sequences occurring rarely in noisy behavioural data is key to understanding the behavioural response to a distributed stimulus in unrestrained animals. Existing models seek to describe the dynamics of behaviour or segment individual locomotor episodes rather than to identify the rare and transient sequences of locomotor episodes that make up the behavioural response. To fill this gap, we develop a lexical, hierarchical model of behaviour. We designed an unsupervised algorithm called “BASS” to efficiently identify and segment recurring behavioural action sequences transiently occurring in long behavioural recordings. When applied to navigating larval zebrafish, BASS extracts a dictionary of remarkably long, non-Markovian sequences consisting of repeats and mixtures of slow forward and turn bouts. Applied to a novel chemotaxis assay, BASS uncovers chemotactic strategies deployed by zebrafish to avoid aversive cues consisting of sequences of fast large-angle turns and burst swims. In a simulated dataset of soaring gliders climbing thermals, BASS finds the spiraling patterns characteristic of soaring behaviour. In both cases, BASS succeeds in identifying rare action sequences in the behaviour deployed by freely moving animals. BASS can be easily incorporated into the pipelines of existing behavioural analyses across diverse species, and even more broadly used as a generic algorithm for pattern recognition in low-dimensional sequential data.

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Gugole, Federica, Luc E. Coffeng, Wouter Edeling, Benjamin Sanderse, Sake J. de Vlas, and Daan Crommelin. "Uncertainty quantification and sensitivity analysis of COVID-19 exit strategies in an individual-based transmission model." PLOS Computational Biology 17, no. 9 (September 17, 2021): e1009355. http://dx.doi.org/10.1371/journal.pcbi.1009355.

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Many countries are currently dealing with the COVID-19 epidemic and are searching for an exit strategy such that life in society can return to normal. To support this search, computational models are used to predict the spread of the virus and to assess the efficacy of policy measures before actual implementation. The model output has to be interpreted carefully though, as computational models are subject to uncertainties. These can stem from, e.g., limited knowledge about input parameters values or from the intrinsic stochastic nature of some computational models. They lead to uncertainties in the model predictions, raising the question what distribution of values the model produces for key indicators of the severity of the epidemic. Here we show how to tackle this question using techniques for uncertainty quantification and sensitivity analysis. We assess the uncertainties and sensitivities of four exit strategies implemented in an agent-based transmission model with geographical stratification. The exit strategies are termed Flattening the Curve, Contact Tracing, Intermittent Lockdown and Phased Opening. We consider two key indicators of the ability of exit strategies to avoid catastrophic health care overload: the maximum number of prevalent cases in intensive care (IC), and the total number of IC patient-days in excess of IC bed capacity. Our results show that uncertainties not directly related to the exit strategies are secondary, although they should still be considered in comprehensive analysis intended to inform policy makers. The sensitivity analysis discloses the crucial role of the intervention uptake by the population and of the capability to trace infected individuals. Finally, we explore the existence of a safe operating space. For Intermittent Lockdown we find only a small region in the model parameter space where the key indicators of the model stay within safe bounds, whereas this region is larger for the other exit strategies.

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Kumar, Biresh, Sharmistha Roy, Anurag Sinha, Celestine Iwendi, and Ľubomíra Strážovská. "E-Commerce Website Usability Analysis Using the Association Rule Mining and Machine Learning Algorithm." Mathematics 11, no. 1 (December 21, 2022): 25. http://dx.doi.org/10.3390/math11010025.

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The overall effectiveness of a website as an e-commerce platform is influenced by how usable it is. This study aimed to find out if advanced web metrics, derived from Google Analytics software, could be used to evaluate the overall usability of e-commerce sites and identify potential usability issues. It is simple to gather web indicators, but processing and interpretation take time. This data is produced through several digital channels, including mobile. Big data has proven to be very helpful in a variety of online platforms, including social networking and e-commerce websites, etc. The sheer amount of data that needs to be processed and assessed to be useful is one of the main issues with e-commerce today as a result of the digital revolution. Additionally, on social media a crucial growth strategy for e-commerce is the usage of BDA capabilities as a guideline to boost sales and draw clients for suppliers. In this paper, we have used the KMP algorithm-based multivariate pruning method for web-based web index searching and different web analytics algorithm with machine learning classifiers to achieve patterns from transactional data gathered from e-commerce websites. Moreover, through the use of log-based transactional data, the research presented in this paper suggests a new machine learning-based evaluation method for evaluating the usability of e-commerce websites. To identify the underlying relationship between the overall usability of the eLearning system and its predictor factors, three machine learning techniques and multiple linear regressions are used to create prediction models. This strategy will lead the e-commerce industry to an economically profitable stage. This capability can assist a vendor in keeping track of customers and items they have viewed, as well as categorizing how customers use their e-commerce emporium so the vendor can cater to their specific needs. It has been proposed that machine learning models, by offering trustworthy prognoses, can aid in excellent usability. Such models might be incorporated into an online prognostic calculator or tool to help with treatment selection and possibly increase visibility. However, none of these models have been recommended for use in reusability because of concerns about the deployment of machine learning in e-commerce and technical issues. One problem with machine learning science that needs to be solved is explainability. For instance, let us say B is 10 and all the people in our population are even. The hash function’s behavior is not random since only buckets 0, 2, 4, 6, and 8 can be the value of h(x). However, if B = 11, we would find that 1/11th of the even integers is transmitted to each of the 11 buckets. The hash function would work well in this situation.

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Carmen, Berevoescu Ileana. "Mathematical Models for Nonlinear Soil Behavior." Romanian Journal of Transport Infrastructure 6, no. 2 (December 1, 2017): 45–52. http://dx.doi.org/10.1515/rjti-2017-0059.

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Abstract Actually, the seismic movement has an irregular cyclic character.This can be equivalent to a determined number of uniform cyclical stresses equivalent in terms of effect. Modeling the behavior of the soil to cyclical stress, is usually done, by establishing a relationship for primary loading like τ = f (γ) and after drawing the diagram “effortless strain curve”, in which τ is the stress, and γ is shear deformation. For modeling nonlinear behavior of the soil, we used like nonlinear models. The best known are the hyperbolic model and the Ramberg-Osgood model.

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Manrai, Ajay K. "Mathematical models of brand choice behavior." European Journal of Operational Research 82, no. 1 (April 1995): 1–17. http://dx.doi.org/10.1016/0377-2217(94)00236-6.

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., Bahodir Boltayevich Muminov. "THE MATHEMATICAL MODELS OF SEARCHING DATA IN THE CENTERS OF INFORMATION RESOURCES." International Journal of Research in Engineering and Technology 05, no. 10 (October 25, 2016): 43–46. http://dx.doi.org/10.15623/ijret.2016.0510007.

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Lobaty, A. A., and V. Y. Stepanov. "PARAMETRIC IDENTIFICATION OF STOCHASTIC SYSTEM BY NON-GRADIENT RANDOM SEARCHING." Science & Technique 16, no. 3 (May 26, 2017): 256–61. http://dx.doi.org/10.21122/2227-1031-2017-16-3-256-261.

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At this moment we know a great variety of identification objects, tasks and methods and its significance is constantly increasing in various fields of science and technology. The identification problem is dependent on a priori information about identification object, besides that the existing approaches and methods of identification are determined by the form of mathematical models (deterministic, stochastic, frequency, temporal, spectral etc.). The paper considers a problem for determination of system parameters (identification object) which is assigned by the stochastic mathematical model including random functions of time. It has been shown that while making optimization of the stochastic systems subject to random actions deterministic methods can be applied only for a limited approximate optimization of the system by taking into account average random effects and fixed structure of the system. The paper proposes an algorithm for identification of parameters in a mathematical model of the stochastic system by non-gradient random searching. A specific feature of the algorithm is its applicability practically to mathematic models of any type because the applied algorithm does not depend on linearization and differentiability of functions included in the mathematical model of the system. The proposed algorithm ensures searching of an extremum for the specified quality criteria in terms of external uncertainties and limitations while using random searching of parameters for a mathematical model of the system. The paper presents results of the investigations on operational capability of the considered identification method while using mathematical simulation of hypothetical control system with a priori unknown parameter values of the mathematical model. The presented results of the mathematical simulation obviously demonstrate the operational capability of the proposed identification method.

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Song, Yong, Yibin Li, Caihong Li, and Xin Ma. "Mathematical Modeling and Analysis of Multirobot Cooperative Hunting Behaviors." Journal of Robotics 2015 (2015): 1–8. http://dx.doi.org/10.1155/2015/184256.

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This paper presents a mathematical model of multirobot cooperative hunting behavior. Multiple robots try to search for and surround a prey. When a robot detects a prey it forms a following team. When another “searching” robot detects the same prey, the robots form a new following team. Until four robots have detected the same prey, the prey disappears from the simulation and the robots return to searching for other prey. If a following team fails to be joined by another robot within a certain time limit the team is disbanded and the robots return to searching state. The mathematical model is formulated by a set of rate equations. The evolution of robot collective hunting behaviors represents the transition between different states of robots. The complex collective hunting behavior emerges through local interaction. The paper presents numerical solutions to normalized versions of the model equations and provides both a steady state and a collaboration ratio analysis. The value of the delay time is shown through mathematical modeling to be a strong factor in the performance of the system as well as the relative numbers of the searching robots and the prey.

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Mochalov, Vladimir, and Anastasia Mochalova. "Search for geophysical structures by their mathematical models and samples." E3S Web of Conferences 127 (2019): 02024. http://dx.doi.org/10.1051/e3sconf/201912702024.

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When we analyze geophysical data, the task of searching for structures by their samples and mathematical models often appears. We propose to use deep neural networks (DNN) to search and detect the forms of geophysical structures. At the same time, both the structure samples themselves and the synthesized structure samples according to their mathematical models act as a training dataset. End-to-end demonstration examples of the highlighting of reflection traces from different layers of the ionosphere in the ionograms, as well as the highlighting of whistler forms in the VLF spectrograms are presented.

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Jacobson, A. "Mathematical models correctly predict cell cycle behavior." Computing in Science & Engineering 5, no. 2 (March 2003): 8. http://dx.doi.org/10.1109/mcise.2003.1182955.

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Tsibulsky, Vladimir, and Andrew Norman. "Mathematical Models of Behavior of Individual Animals." Current Pharmaceutical Design 13, no. 15 (May 1, 2007): 1571–95. http://dx.doi.org/10.2174/138161207780765873.

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Akhmetov, R. T., V. V. Mukhametshin, L. S. Kuleshova, and O. A. Grezina. "Using capillary pressure curves when searching for analog objects." Journal of Physics: Conference Series 2176, no. 1 (June 1, 2022): 012010. http://dx.doi.org/10.1088/1742-6596/2176/1/012010.

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Abstract In this work, the capillary pressure curves were approximated using fractions of various types for the conditions of individual oil deposits of the West Siberian oil and gas province. A mathematical model of capillary curves in the coordinate axes of dimensionless time from the normalized water saturation has been created. The obtained models make it possible to search for analog objects and effectively solve the problems of increasing the efficiency of developing low-profitable deposits with hard-to-recover reserves based on comparing the regression equations of generalized models with models of the required deposits.

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Price, Andrew R., Richard J. Myerscough, Ivan I. Voutchkov, Robert Marsh, and Simon J. Cox. "Multi-objective optimization of GENIE Earth system models." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 367, no. 1898 (July 13, 2009): 2623–33. http://dx.doi.org/10.1098/rsta.2009.0039.

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The tuning of parameters in climate models is essential to provide reliable long-term forecasts of Earth system behaviour. We apply a multi-objective optimization algorithm to the problem of parameter estimation in climate models. This optimization process involves the iterative evaluation of response surface models (RSMs), followed by the execution of multiple Earth system simulations. These computations require an infrastructure that provides high-performance computing for building and searching the RSMs and high-throughput computing for the concurrent evaluation of a large number of models. Grid computing technology is therefore essential to make this algorithm practical for members of the GENIE project.

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Hastings, Alan. "Mathematical Models of Population Biology." Ecology 69, no. 4 (August 1988): 1311–12. http://dx.doi.org/10.2307/1941295.

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Mazur, James E. "MATHEMATICAL MODELS AND THE EXPERIMENTAL ANALYSIS OF BEHAVIOR." Journal of the Experimental Analysis of Behavior 85, no. 2 (March 2006): 275–91. http://dx.doi.org/10.1901/jeab.2006.65-05.

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Zenyuk, Dmitry Alexeevich, Georgii Gennadyevich Malinetskii, and Dmitry Sergeyevich Faller. "Mathematical models of corruptional behavior with imperfect audit." Keldysh Institute Preprints, no. 53 (2018): 1–20. http://dx.doi.org/10.20948/prepr-2018-53.

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Millan, Alberto Jovani, Suzanne Sindi, and Jennifer Manilay. "Predicting Natural Killer Cell Behavior with Mathematical Models." Journal of Immunology 202, no. 1_Supplement (May 1, 2019): 65.5. http://dx.doi.org/10.4049/jimmunol.202.supp.65.5.

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Abstract Natural killer (NK) cells are specialized lymphocytes with an innate ability to eliminate virally infected and cancerous cells, but the mechanisms that control NK cell development and cytotoxicity are incompletely understood. We hypothesize mathematical models can be used to predict how to direct NK cell development toward mature NK cells. We observed Sostdc1-knockout (KO) mice to display a partial NK cell developmental block. Building from these studies, a best fit model was simulated in which rates of transition and differentiation and cell death was determined by ordinary differential equations of deterministic compartmental models. This approach indicated that NK cell proliferation rates are not necessary to predict WT and KO population outcomes. We further hypothesize that clusters of highly cytotoxic NK cells can be identified computationally, using a combination of Ly49 receptor expression, in vitro and in vivo cytotoxicity assays using β2m−/− targets, and viSNE analysis of flow cytometry data. Sostdc1-KO NK cells also display defective cytotoxicity. We identified that KO splenic CD27+CD11b+ transitional NK cells express lower frequencies of inhibitory Ly49G2, but higher frequencies of activating Ly49H+ and D+ cells. Our viSNE results identified 3 NK cell clusters displaying a “superactive” phenotype that were virtually absent in KO mice; consistent with our observations of their hyporesponsiveness. Taken together, these data support a role for Sostdc1 in the regulation of NK cells and could provide insights into novel biological parameters to expand active NK cell numbers with high killing efficiency for immunotherapies.

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Hezam, Ibrahim M., and Moddassir k. Nayeem. "A Systematic Literature Review on Mathematical Models of Humanitarian Logistics." Symmetry 13, no. 1 (December 23, 2020): 11. http://dx.doi.org/10.3390/sym13010011.

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Humanitarian logistics (HL) is considered one of the most significant issues of disaster operations and management. Thus, HL operation should be viable enough to function well under the uncertain and complex nature of the disaster. Many difficulties in pre-and post-disaster phases bring both human and economic losses. Therefore, it is essential to make sure that the HL operations are designed efficiently. In the last two decades, several publications have emphasized efficient HL operations and proposed several mathematical models and algorithms to increase the efficiency of HL operations and motivated the necessity of a systematic literature review. A systematic literature review is deemed pertinent due to its transparent and detailed article searching procedure. In this study, due to the importance of the mathematical optimization model, we reviewed more than one hundred articles published between 2000 and 2020 to investigate the optimization models in the field of HL. We classified the optimization models into three main problems: facility location problems, relief distribution, and mass evacuation where each of the classified areas includes both deterministic and non-deterministic models.

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Aberšek, Boris, and Samo Mikluš. "Models for Optimization of Gantry Crane Main Girder." Key Engineering Materials 348-349 (September 2007): 657–60. http://dx.doi.org/10.4028/www.scientific.net/kem.348-349.657.

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The optimization is the process of searching for the best results in a certain load case. Complete definition of optimization includes three conditions, which are closely connected: • optimization target, defined with object function, • subject of optimization, • optimization methods. The object functions can be different process parameters such as costs, manufacturing time, costefficiency, productivity etc. In designing of the structures such as a crane there is a tendency particularly towards reducing the weight of steel structures with the same load-carrying capacity. Thus the object function can be the volume, weight or mass of the structure. In the paper we will devote ourselves to optimization of truss structures-gantry crane mean girder by means of the FEM. This method has become indispensable in all areas of analyses of structures in combination with mathematical modeling and mathematical methods of optimization and is particularly of assistance to designers in conceiving the steel structures.

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Lan, Chun Hsiung, and Su Yee Ma. "Construct an INLP Mathematical Model to Solve the Two-Sided Assembly Line Balancing Problem of Type-3." Advanced Materials Research 383-390 (November 2011): 4302–5. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.4302.

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This study discusses construct an Integer Nonlinear Programming (INLP) mathematical model is presented to solve the Two-Sided assembly line balancing problem (TALB) of Type-3. The mathematical models proposed in this paper are constructed by the syntax of Lingo, and the built-in “global solver” is selected as the solving method to conduct the searching of global optimum solutions. Therefore, the Type-3 of TALB for optimal distribution by the mathematical models proposed in this study to be solved. This study creates a highly repeated characteristic because of the adoption of Lingo packaged software. Finally, the tests are carried out on a well-known benchmark set of problem, and experimental results demonstrate that the proposed model is efficient.

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Yongwang, Liu, Liu Yu-ming, Qiu Heng-bin, and Bai Yan-feng. "A New Mathematical Method for Solving Cuttings Transport Problem of Horizontal Wells: Ant Colony Algorithm." Mathematical Problems in Engineering 2017 (2017): 1–8. http://dx.doi.org/10.1155/2017/7898647.

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Cuttings transport problem has long been recognized as one of the key difficulties in drilling horizontal wells, and the models in cuttings transport research are usually formulated with highly nonlinear equations set. When using Newton methods to solve real engineering problems with nonlinear equations set, the problems of result dependence on initial values, Jacobian matrix singularity, and variable outflow of its definition domain in iterations are three of the often-encountered difficulties. In this paper, the ant colony algorithm is applied to solve the two-layer cuttings transport model with highly nonlinear equations set. The solution-searching process of solving nonlinear equations set is transformed into an optimization process of searching the minimum value of an objective function by applying ant colony algorithm. Analyzing the results of the example, it can be concluded that ant colony algorithm can be used to solve the highly nonlinear cuttings transport model with good solution accuracy; transforming the solution-searching process of solving nonlinear equations set into an optimization process of searching the minimum value of the objective function is necessary; the real engineering problem should be simplified as much as possible to decrease the number of unknown variables and facilitate the use of ant colony algorithm.

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Urbina, Angel, and Thomas Paez. "Statistical Validation of Structural Dynamics Models." Journal of the IEST 46, no. 1 (September 14, 2003): 141–48. http://dx.doi.org/10.17764/jiet.46.1.f430423634885g67.

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There is an increasing reliance in the engineering community on the use of mathematical models to characterize physical system behavior. This is happening even though mathematical models rarely simulate real system behavior perfectly. Due to this reliance, we require objective, well-founded mathematical techniques for model validation. This paper develops a formal approach to the validation of mathematical models of structural dynamics systems. It uses a probabilistic/statistical approach to the characterization of an important measure of behavior of dynamic systems subjected to random excitations, and seeks to validate a mathematical model in a statistical sense. An example is presented.

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Katkov, Mikhail, Michelangelo Naim, Antonios Georgiou, and Misha Tsodyks. "Mathematical models of human memory." Journal of Mathematical Physics 63, no. 7 (July 1, 2022): 073303. http://dx.doi.org/10.1063/5.0088823.

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Human memory is an incredibly complex system of vast capacity but often unreliable. Measuring memory for realistic material, such as narratives, is quantitatively challenging as people rarely remember narratives verbatim. Cognitive psychologists developed experimental paradigms involving randomly collected lists of items that make possible quantitative measures of performance in memory tasks, such as recall and recognition. Here, we describe a set of mathematical models designed to predict the results of these experiments. The models are based on simple underlying assumptions and surprisingly agree with experimental results quite well, in addition to that they exhibit quite interesting mathematical behavior that can partially be understood analytically.

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Bartnik, Ryszard, Waldemar Skomudek, and Aleksandra Otawa. "The Methodology and Mathematical Models Searching for the Optimal Investment Strategy in Sources of Heat." Pomiary Automatyka Robotyka 20, no. 4 (December 29, 2016): 51–58. http://dx.doi.org/10.14313/par_222/51.

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Sumin, V. I., A. V. Dushkin, and T. E. Smolentseva. "Mathematical Models to Determine Stable Behavior of Complex Systems." Journal of Physics: Conference Series 1015 (May 2018): 032136. http://dx.doi.org/10.1088/1742-6596/1015/3/032136.

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Santillán, Moisés, and Michael C. Mackey. "Dynamic behavior in mathematical models of the tryptophan operon." Chaos: An Interdisciplinary Journal of Nonlinear Science 11, no. 1 (2001): 261. http://dx.doi.org/10.1063/1.1336806.

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KLEIN, EILI, RAMANAN LAXMINARAYAN, DAVID L. SMITH, and CHRISTOPHER A. GILLIGAN. "Economic incentives and mathematical models of disease." Environment and Development Economics 12, no. 5 (October 2007): 707–32. http://dx.doi.org/10.1017/s1355770x0700383x.

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The fields of epidemiological disease modeling and economics have tended to work independently of each other despite their common reliance on the language of mathematics and exploration of similar questions related to human behavior and infectious disease. This paper explores the benefits of incorporating simple economic principles of individual behavior and resource optimization into epidemiological models, reviews related research, and indicates how future cross-discipline collaborations can generate more accurate models of disease and its control to guide policy makers.

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Marchuk, E. A., A. V. Kireeva, and Ya V. Kalinin. "Mathematical Modeling of Molecular Compounds of Adamantane Derivatives." Vestnik Tambovskogo gosudarstvennogo tehnicheskogo universiteta 26, no. 3 (2020): 402–10. http://dx.doi.org/10.17277/vestnik.2020.03.pp.402-410.

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The article deals with the problems of mathematical modeling of chemical compounds by the example of adamantane derivatives. As the main me-thod, matrix forms of representation of the molecular structure are used, the use of which should be recognized as the most convenient for constructing mathematical models in the MATLAB package. The use of the theory of molecular assemblies when considering chemical compounds from the perspective of evolutionary modeling is substantiated. The possibility of formulating the problem of searching for the structure of chemical compounds of adamantane derivatives in the form of an optimization problem using genetic algorithms is shown. An attempt is made to generalize the results of modeling adamantane derivatives to a wider class of molecular compounds with a complex spatial structure.

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De Gaetano, Andrea, Thomas Hardy, Benoit Beck, Eyas Abu-Raddad, Pasquale Palumbo, Juliana Bue-Valleskey, and Niels Pørksen. "Mathematical models of diabetes progression." American Journal of Physiology-Endocrinology and Metabolism 295, no. 6 (December 2008): E1462—E1479. http://dx.doi.org/10.1152/ajpendo.90444.2008.

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Few attempts have been made to model mathematically the progression of type 2 diabetes. A realistic representation of the long-term physiological adaptation to developing insulin resistance is necessary for effectively designing clinical trials and evaluating diabetes prevention or disease modification therapies. Writing a good model for diabetes progression is difficult because the long time span of the disease makes experimental verification of modeling hypotheses extremely awkward. In this context, it is of primary importance that the assumptions underlying the model equations properly reflect established physiology and that the mathematical formulation of the model give rise only to physically plausible behavior of the solutions. In the present work, a model of the pancreatic islet compensation is formulated, its physiological assumptions are presented, some fundamental qualitative characteristics of its solutions are established, the numerical values assigned to its parameters are extensively discussed (also with reference to available cross-sectional epidemiologic data), and its performance over the span of a lifetime is simulated under various conditions, including worsening insulin resistance and primary replication defects. The differences with respect to two previously proposed models of diabetes progression are highlighted, and therefore, the model is proposed as a realistic, robust description of the evolution of the compensation of the glucose-insulin system in healthy and diabetic individuals. Model simulations can be run from the authors' web page.

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Lebowitz, Joel L., Errico Presutti, and Herbert Spohn. "Microscopic models of hydrodynamic behavior." Journal of Statistical Physics 51, no. 5-6 (June 1988): 841–62. http://dx.doi.org/10.1007/bf01014887.

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Smirnov, Sergei Alevtinovich. "Digital school: Searching for Explanatory Models. Part 1." Science for Education Today 11, no. 6 (December 30, 2021): 62–79. http://dx.doi.org/10.15293/2658-6762.2106.04.

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Introduction. The purpose of this study was to analyze L. S. Vygotsky’s cultural-historical psychology from the perspective of distinguishing the structure of the act of development within its framework and understanding its explanatory potential as a whole. This analysis enables to clarify and understand the essence of the digital and virtual shift. Moreover, it is required in order to overcome the limitations associated with the currently dominant behavioral models, which are used by researchers in their attempts to explain and describe the phenomenon of the influence of digital technologies on people, in particular, on schoolchildren and students. Materials and Methods. The paper considers the concept derived from L. S. Vygotsky’s cultural-historical psychology, which is proposed to be adopted as a basic one in order to build an explanatory model used by the author to describe and comprehend the phenomenon of transformation of the human development process in the new reality of the digital environment. Results. The article introduces the basic principles and provisions, the explanatory model is built on, concerning the role of symbolic-instrumental mediation in human development, the role of an adult as a mediator, the structure of the act of thinking and the act of development, the basic mechanism of mastering a person's behavior, which permeates the formation of higher mental functions. The author compares this explanatory model and the behavioral model used in most modern research investigations that examine the impact of digital technologies on schoolchildren and students. Conclusions. The findings show that the student is presented in the behavioral model as a passive reactive being that reacts to external stimuli. In this sense, a human being is not treated as a personality with highest abilities, but is considered as a function. The proposed model cannot be used to explain and comprehend modern development processes.

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Tedeschi, Luís Orlindo, Danny Gene Fox, Roberto Daniel Sainz, Luís Gustavo Barioni, Sérgio Raposo de Medeiros, and Celso Boin. "Mathematical models in ruminant nutrition." Scientia Agricola 62, no. 1 (January 2005): 76–91. http://dx.doi.org/10.1590/s0103-90162005000100015.

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Mathematical models can be used to improve performance, reduce cost of production, and reduce nutrient excretion by accounting for more of the variation in predicting requirements and feed utilization in each unique production situation. Mathematical models can be classified into five or more categories based on their nature and behavior. Determining the appropriate level of aggregation of equations is a major problem in formulating models. The most critical step is to describe the purpose of the model and then to determine the appropriate mix of empirical and mechanistic representations of physiological functions, given development and evaluation dataset availability, inputs typically available and the benefits versus the risks of use associated with increased sensitivity. We discussed five major feeding systems used around the world. They share common concepts of energy and nutrient requirement and supply by feeds, but differ in structure and application of the concepts. Animal models are used for a variety of purposes, including the simple description of observations, prediction of responses to management, and explanation of biological mechanisms. Depending upon the objectives, a number of different approaches may be used, including classical algebraic equations, predictive empirical relationships, and dynamic, mechanistic models. The latter offer the best opportunity to make full use of the growing body of knowledge regarding animal biology. Continuing development of these types of models and computer technology and software for their implementation holds great promise for improvements in the effectiveness with which fundamental knowledge of animal function can be applied to improve animal agriculture and reduce its impact on the environment.

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Drin, Bohdan, Iryna Drin, and Svitlana Drin. "THE NONLINEAR MODEL OF BEHAVIOR OF TWO COMPETITIVE FIRMS." BULLETIN OF CHERNIVTSI INSTITUTE OF TRADE AND ECONOMICS I, no. 81 (March 15, 2021): 115–28. http://dx.doi.org/10.34025/2310-8185-2021-1.81.08.

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The practical task of economics lies in applying the methods of substantiating its decisions. For economics, the main method is the modeling of economic phenomena and processes and, above all, mathematical modeling, which has been stipulated by the presence of stable MATHEMATICAL METHODS, MODELS AND INFORMATION TECHNOLOGIES IN ECONOMY Issue I (81), 2021 117 quantitative patterns and the possibility of a formalized description of many economic processes. The economic-mathematical model contains a system of equations of linear and nonlinear units that promote a mathematical description of economic processes and phenomena, consists of a set of variables and parameters and serves to study these processes and control them. Dynamic models of the economy describe it in development, as well as provide a detailed description of technological methods of production. Mathematical description of dynamic models is carried out with the use of a system of differential equations (in models with continuous time), difference equations (in models with discrete time), as well as systems of algebraic equations. It is important that the investigation of various economic issues has led to the development of the mathematical apparatus. In linear algebra, productive matrices are caused by the studies of intersectoral balance, whereas mathematical programming arose in the course of researching the optimal plan for the distribution of limited resources. In a similar way, there emerged the theory of economic indices and econometrics, the theory of production functions and the theory of consumption, the theory of general economic balance and social welfare, the theory of optimal economic growth. The paper under studies deals with the dynamic economic behavior of two competing objects, whose mathematical model is a nonlinear nonlocal problem for a system of ordinary differential equations with variable coefficients and argument deviation. The dynamic mathematical model is based on the assumption that the volume of output of both firms is determined by such factors on which output depends linearly. The model under discussion includes nonlinear factors, which describe the level of distrust of the competitors and depend on the time of observations and production volumes in previous moments, because the latter significantly affect the production activities of the firm. Such mathematical models are called time-delayed models.

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Stroganov, V. F., R. A. Kayumov, A. S. Akhmetshin, and I. V. Stroganov. "Mathematical models of behavior of polymer material with shape memory." Polymer Science Series D 4, no. 4 (October 2011): 334–38. http://dx.doi.org/10.1134/s1995421211040137.

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Garnett, G. P., and R. M. Anderson. "Sexually Transmitted Diseases And Sexual Behavior: Insights From Mathematical Models." Journal of Infectious Diseases 174, Supplement 2 (October 1, 1996): S150—S161. http://dx.doi.org/10.1093/infdis/174.supplement_2.s150.

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Journal articles on the topic 'Searching behavior – Mathematical models'

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