Artigos de revistas: "Ordered Weights Average"

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Espinoza-Audelo, Luis F., Ernesto León-Castro, Marycruz Olazabal-Lugo, José M. Merigó e Anna M. Gil-Lafuente. "Using Ordered Weighted Average for Weighted Averages Inflation". International Journal of Information Technology & Decision Making 19, n.º 02 (março de 2020): 601–28. http://dx.doi.org/10.1142/s0219622020500066.

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This paper presents the ordered weighted average weighted average inflation (OWAWAI) and some extensions using induced and heavy aggregation operators and presents the generalized operators and some of their families. The main advantage of these new formulations is that they can use two different sets of weighting vectors and generate new scenarios based on the reordering of the arguments with the weights. With this idea, it is possible to generate new approaches that under- or overestimate the results according to the knowledge and expertise of the decision-maker. The work presents an application of these new approaches in the analysis of the inflation in Chile, Colombia, and Argentina during 2017.

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S, Charles, e Dr L. Arockiam. "Fuzzy Weighted Ordered Weighted Average-Gaussian Mixture Model for Feature Reduction". INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 4, n.º 2 (30 de novembro de 2005): 694–712. http://dx.doi.org/10.24297/ijct.v4i2c2.4192.

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Feature reduction finds the optimal feature subset using machine learning techniques and evaluation criteria. Some of the irrelevant features are existed in the real-world datasets that should be removed by using the multi criterion decision approach. The relevant features are determined by using the WOWA criteria in fuzzy set. There are two important criteria are considered such as preferential weights and importance weights of features. These weights are used to find the irrelevant features and they are removed from the mixture. In this context, WOWA operator has the capability of assigning the preferential weights and important weights to the features. It helps to obtain the irrelevant, by selecting the relevant features using the weights in the feature reduction process. The objective of this paper is to propose a FWOWA approach helps to discard the irrelevant features by avoiding the overfitting and improve the accuracy of the cluster. The irrelevant features are determined by applying WOWA. By applying WOWA, the irrelevant features are examined and it is removed from the Gaussian Mixture using (RPEM).Â Â Â

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Ruiz-Morales, Betzabe, Irma Cristina Espitia-Moreno, Victor G. Alfaro-Garcia e Ernesto Leon-Castro. "Sustainable Development Goals Analysis with Ordered Weighted Average Operators". Sustainability 13, n.º 9 (7 de maio de 2021): 5240. http://dx.doi.org/10.3390/su13095240.

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The present research proposes a new method to analyze the sustainable development goals (SDGs) index using ordered weighted average (OWA) operators. To develop this method, five experts evaluated and designated the relative importance of each of the 17 SDGs defined by the United Nations (UN), and with the use of the OWA and prioritized OWA (POWA) operators, rankings were generated. With the results, it is possible to visualize that the ranking of countries can change depending on the weights related to each SDG because the OWA and POWA operator methods can capture the uncertainty of the phenomenon.

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Yoshida, Yuji. "Ordered Weighted Averages on Intervals and the Sub/Super-Additivity". Journal of Advanced Computational Intelligence and Intelligent Informatics 17, n.º 4 (20 de julho de 2013): 520–25. http://dx.doi.org/10.20965/jaciii.2013.p0520.

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This paper deals with continuous Ordered Weighted Averages (OWA) on a closed interval and investigates their fundamental properties. In this paper, we focus on OWA with a truncation weight and derive the subadditivity of a top-concentrated average. We then deal with OWA from the bottom and investigate their relations. The subadditivity for OWA with monotone weights is also discussed, then OWA based on probability are demonstrated and value-at-risks are explained as an example.

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Savarimuthu, Charles, e Arockiam L. "Pairwise Fuzzy Ordered Weighted Average Algorithm-Gaussian Mixture Model for Feature Reduction". INTERNATIONAL JOURNAL OF COMPUTERS & TECHNOLOGY 6, n.º 1 (30 de maio de 2013): 287–301. http://dx.doi.org/10.24297/ijct.v6i1.4457.

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Feature Reduction is a kind of dimensionality reduction of feature space. There are a number of approaches are used to identify the significant features but they are not using the weighing approach. The weighing approach is quite useful for obtaining the significant features and removing the insignificant and irrelevant features using OWA formulation. The aim of this approach is to obtain the significant features and removing insignificant features by using the pairwise approach. This approach is helpful to find the weights of pairwise features at the same time, which leads to remove the insignificant features from the feature space using OWA. The significance of the OWA formulation is that, the paired features are identified in priori and their sum of weights are equal to 1. OWA criterion is introduced to obtain the significant features that are useful for predicting the accuracy of the cluster in GMM.

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Ogryczak, Włodzimierz. "Reference Point Method with Importance Weighted Partial Achievements". Journal of Telecommunications and Information Technology, n.º 4 (26 de junho de 2023): 17–25. http://dx.doi.org/10.26636/jtit.2008.4.893.

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The reference point method (RPM) is based on the so-called augmented max-min aggregation where the worst individual achievement maximization process is additionally regularized with the average achievement. In order to avoid inconsistencies caused by the regularization, we replace it with the ordered weighted average (OWA) which combines all the individual achievements allocating the largest weight to the worst achievement, the second largest weight to the second worst achievement, and so on. Further following the concept of the weighted OWA (WOWA) we incorporate the importance weighting of several achievements into the RPM. Such a WOWA RPM approach uses importance weights to affect achievement importance by rescaling accordingly its measure within the distribution of achievements rather than by straightforward rescaling of achievement values. The recent progress in optimization methods for ordered averages allows us to implement the WOWA RPM quite effectively as extension of the original constraints and criteria with simple linear inequalities.

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Kuz’mina, N. E., S. V. Moiseev, V. I. Krylov, V. A. Yashkir e V. A. Merkulov. "Quantitative determination of the average molecular weights of dextrans by diffusion ordered NMR spectroscopy". Journal of Analytical Chemistry 69, n.º 10 (21 de setembro de 2014): 953–59. http://dx.doi.org/10.1134/s1061934814100086.

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Wankhade, Sandeep, Manoj Sahni, Cristhian Mellado-Cid e Ernesto Leon-Castro. "Using the Ordered Weighted Average Operator to Gauge Variation in Agriculture Commodities in India". Axioms 12, n.º 10 (18 de outubro de 2023): 985. http://dx.doi.org/10.3390/axioms12100985.

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Agricultural product prices are subject to various uncertainties, including unpredictable weather conditions, pest infestations, and market fluctuations, which can significantly impact agricultural yields and productivity. Accurately assessing and understanding price is crucial for farmers, policymakers, and stakeholders in the agricultural sector to make informed decisions and implement appropriate risk management strategies. This study used the ordered weighted average (OWA) operator and its extensions as mathematical aggregation techniques incorporating ordered weights to capture and evaluate the factors influencing price variation. By generating different vectors related to different inputs to the traditional formulation, it is possible to aggregate information to calculate and provide a new view of the outcomes. The results of this research can help enhance risk management practices in agriculture and support decision-making processes to mitigate the adverse effects of price.

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Freixas, Josep. "An Aggregation Rule Based on the Binomial Distribution". Mathematics 10, n.º 23 (23 de novembro de 2022): 4418. http://dx.doi.org/10.3390/math10234418.

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Many decision-making situations require the evaluation of several voters or agents. In a situation where voters evaluate candidates, the question arises of how best to aggregate evaluations so as to compare the candidates. The aim of this work is to propose a method of aggregating the evaluations of the voters, which has outstanding properties and serve as a potential evaluative tool in many contexts. Ordered weighted averages is a family of rules appropriate for studying this problem. In this paper, I propose as a solution an ordered weighted average that satisfies compelling properties and whose weights are derived from the binomial distribution.

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Majdan, Michał. "On Subjective Trust Management". Journal of Telecommunications and Information Technology, n.º 4 (26 de junho de 2023): 26–31. http://dx.doi.org/10.26636/jtit.2008.4.894.

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Trust and reputation management is gaining nowadays more attention then ever as online commodity exchange and other open virtual societies became a widespread reality. Most widely used computational models use reputation metrics as global property assigned to each party. More sophisticated models try to use reputation as subjective property. While introducing subjective reputation there arise a need to model preferences of agents. In this paper we propose to use weighted ordered weighted average (WOWA) operator to support the decision maker in assessing available evidence about other’s party behavior. The WOWA aggregation is defined by two weighting vectors: the preferential weights assigned to the ordered quantities and the importance weights assigned to several attributes. It allows one to express both the preference regarding sources of information by the corresponding importance weights and the compensation between attribute values aggregated by the preferential weights.

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BALLINI, R., e R. R. YAGER. "LINEAR DECAYING WEIGHTS FOR TIME SERIES SMOOTHING: AN ANALYSIS". International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 22, n.º 01 (fevereiro de 2014): 23–40. http://dx.doi.org/10.1142/s0218488514500020.

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In this paper, we investigate the use of weighted averaging aggregation operators as techniques for time series smoothing. We analyze the moving average, exponential smoothing methods, and a new class of smoothing operators based on linearly decaying weights from the perspective of ordered weights averaging to estimate a constant model. We examine two important features associated with the smoothing processes: the average age of the data and the expected variance, both defined in terms of the associated weights. We show that there exists a fundamental conflict between keeping the variance small while using the freshest data. We illustrate the flexibility of the smoothing methods with real datasets; that is, we evaluate the aggregation operators with respect to their minimal attainable variance versus average age. We also examine the efficiency of the smoothed models in time series smoothing, considering real datasets. Good smoothing generally depends upon the underlying method's ability to select appropriate weights to satisfy the criteria of both small variance and recent data.

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MARCHANT, T. "MAXIMAL ORNESS WEIGHTS WITH A FIXED VARIABILITY FOR OWA OPERATORS". International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 14, n.º 03 (junho de 2006): 271–76. http://dx.doi.org/10.1142/s021848850600400x.

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When using the ordered weighted average operator, it can happen that one wants to optimize the variability (measured by the entropy (maximal) or by the variance (minimal)) of the weights while keeping the orness of this operator at a fixed level. This has been considered by several authors. Dually, there might be some contexts where one wishes to maximize the orness while guaranteeing some fixed variability. In this paper, we present two algorithms for finding such weights, when the variability is captured by the entropy and by the variance.

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Suo, Meiqin, Jing Zhang, Lixin He, Qian Zhou e Tengteng Kong. "A Study on Evaluating Water Resources System Vulnerability by Reinforced Ordered Weighted Averaging Operator". Mathematical Problems in Engineering 2020 (20 de novembro de 2020): 1–9. http://dx.doi.org/10.1155/2020/5726523.

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Evaluating the vulnerability of a water resources system is a multicriteria decision analysis (MCDA) problem including multiple indictors and different weights. In this study, a reinforced ordered weighted averaging (ROWA) operator is proposed by incorporating extended ordered weighted average operator (EOWA) and principal component analysis (PCA) to handle the MCDA problem. In ROWA, the weights of indicators are calculated based on component score coefficient and percentage of variance, which makes ROWA avoid the subjective influence of weights provided by different experts. Concretely, the applicability of ROWA is verified by assessing the vulnerability of a water resources system in Handan, China. The obtained results can not only provide the vulnerable degrees of the studied districts but also denote the trend of water resources system vulnerability in Handan from 2009 to 2018. And the indictor that most influenced the outcome is per capita GDP. Compared with EOWA referred to various indictor weights, the represented ROWA shows good objectivity. Finally, this paper also provides the vulnerability of the water resource system in 2025 based on ROWA for water management in Handan City.

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Xu, Wei Bin, Qing Jie Zhu e Hai Bo Jia. "The Comprehensive Evaluation Method Based on GIS of Oil well Casing Damage". Advanced Materials Research 807-809 (setembro de 2013): 2595–601. http://dx.doi.org/10.4028/www.scientific.net/amr.807-809.2595.

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Oil well casing damage is one of the security problems in petroleum engineering, it should be paid more attention in oil and gas development. Influence factors of oil well casing damage are very complicated, and the evaluation criteria of each influence factors are different. Therefore, for the assessment of casing damage, should be based on a comprehensive engineering and petroleum geology of the argument, using multi-criteria evaluation method to implement from the safety point of view. The development of multi-criteria evaluation method based on GIS oil well casing damaged isnt only consider the relative importance of each influence factor, but also fully consider the various factors of space walks and order of importance. With the help of IDRISI software, Jinzhou oil production plant in the 25 block as an example, calculating order weights and criteria weights, the comprehensive evaluation of damage to the casing pipe of oil well is made. By comparison of weighted linear combination method and the ordered weighted average (OWA) method, analyzes the ordered weighted average method advantage.

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Ruan, Chuanyang, Xiangjing Chen e Lin Yan. "Fermatean Hesitant Fuzzy Multi-Attribute Decision-Making Method with Probabilistic Information and Its Application". Axioms 13, n.º 7 (4 de julho de 2024): 456. http://dx.doi.org/10.3390/axioms13070456.

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When information is incomplete or uncertain, Fermatean hesitant fuzzy sets (FHFSs) can provide more information to help decision-makers deal with more complex problems. Typically, determining attribute weights assumes that each attribute has a fixed influence. Introducing probability information can enable one to consider the stochastic nature of evaluation data and better quantify the importance of the attributes. To aggregate data by considering the location and importance degrees of each attribute, this paper develops a Fermatean hesitant fuzzy multi-attribute decision-making (MADM) method with probabilistic information and an ordered weighted averaging (OWA) method. The OWA method combines the concepts of weights and sorting to sort and weigh average property values based on those weights. Therefore, this novel approach assigns weights based on the decision-maker’s preferences and introduces probabilities to assess attribute importance under specific circumstances, thereby broadening the scope of information expression. Then, this paper presents four probabilistic aggregation operators under the Fermatean hesitant fuzzy environment, including the Fermatean hesitant fuzzy probabilistic ordered weighted averaging/geometric (FHFPOWA/FHFPOWG) operators and the generalized Fermatean hesitant fuzzy probabilistic ordered weighted averaging/geometric (GFHFPOWA/GFHFPOWG) operators. These new operators are designed to quantify the importance of attributes and characterize the attitudes of decision-makers using a probabilistic and weighted vector. Then, a MADM method based on these proposed operators is developed. Finally, an illustrative example of selecting the best new retail enterprise demonstrates the effectiveness and practicality of the method.

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SU, WEIHUA, YONG YANG, CHONGHUI ZHANG e SHOUZHEN ZENG. "INTUITIONISTIC FUZZY DECISION-MAKING WITH SIMILARITY MEASURES AND OWA OPERATOR". International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 21, n.º 02 (abril de 2013): 245–62. http://dx.doi.org/10.1142/s021848851350013x.

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In this paper, we present a new intuitionistic fuzzy decision-making technique based on similarity measures and the ordered weighted average (OWA) operator. We develop the intuitionistic fuzzy ordered weighted similarity (IFOWS) measure. The main advantage of the IFOWS measure is that it can alleviate the influence of unduly large (or small) deviations on the aggregation results by assigning them low (or high) weights. Moreover, it provides a very general formulation that includes a wide range of aggregation similarity measures and aggregates the input arguments taking the form of intuitionistic fuzzy values rather than exact numbers. We further develop the interval-valued intuitionistic fuzzy ordered weighted similarity (IVIFOWS) measure. Then we apply the developed similarity measures for consensus analysis in group decision-making with intuitionistic fuzzy information. Finally, a practical case is used to illustrate the developed procedures.

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Jiang, Hongren. "An Approach to Multi-attribute Group Decision Making with Trapezoidal Interval Type-2 Fuzzy Sets and Application to Teaching Quality Assessment". Journal of Intelligent Systems 23, n.º 4 (1 de dezembro de 2014): 391–404. http://dx.doi.org/10.1515/jisys-2013-0073.

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AbstractTrapezoidal interval type-2 fuzzy sets (TIT2FSs) are a special kind of type-2 fuzzy sets. TIT2FSs are useful in dealing with fuzziness inherent in decision data and the decision-making process. For multi-attribute group decision-making problems in which the attribute values and attribute weights are TIT2FSs, a new decision-making approach is proposed. On the basis of the concept of barycenters, a new approach to ranking TIT2FSs is given. Four kinds of geometric aggregation operators for TIT2FSs are developed, including the TIT2FS weighted geometric average operator, TIT2FS ordered weighted geometric average operator, TIT2FS hybrid weighted geometric average operator, and extended TIT2FS hybrid weighted geometric average operator. The individual comprehensive values of alternatives are derived through the extended TIT2FS weighted geometric average operators. Using the TIT2FS hybrid weighted geometric average operator and the expert weights, the individual comprehensive values of alternatives are integrated into the collective ones, which are used to rank the alternatives. The practicability and effectiveness of the developed method are illustrated with a teaching quality assessment example.

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Dong, Jiu-Ying, Li-Lian Lin, Feng Wang e Shu-Ping Wan. "Generalized Choquet Integral Operator of Triangular Atanassov’s Intuitionistic Fuzzy Numbers and Application to Multi-Attribute Group Decision Making". International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 24, n.º 05 (outubro de 2016): 647–83. http://dx.doi.org/10.1142/s0218488516500306.

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The purpose of this paper is to propose a new approach to interactive multi-attribute group decision making with triangular Atanassov's intuitionistic fuzzy numbers (TAIFNs). The contribution of this study is fivefold: (1) Minkowski distance between TAIFNs is firstly defined; (2) We define the possibility attitudinal expected values of TAIFNs and thereby present a novel risk attitudinal ranking method of TAIFNs which can sufficiently consider the risk attitude of decision maker; (3) The weighted average operator (TAIFWA) and generalized ordered weighted average (TAIFGWA) operator of TAIFNs are defined as well as the hybrid ordered weighted average (TAIFHOWA) operator; (4) To study the interaction between attributes, we further develop the generalized Choquet (TAIF-GC) integral operator and generalized hybrid Choquet (TAIF-GHC) integral operator of TAIFNs. Their desirable properties are also discussed; (5) The individual overall value of alternative is obtained by TAIF-GC operator and the collective one is derived through TAIFWA operator. Fuzzy measures of attribute subsets and expert weights are objectively derived through constructing multi-objective optimization model which is transformed into the goal programming model to solve. The system analyst selection example verifies effectiveness of the proposed approach.

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Chowdhury, Shahadat, e Ashish Sharma. "Long-Range Niño-3.4 Predictions Using Pairwise Dynamic Combinations of Multiple Models". Journal of Climate 22, n.º 3 (1 de fevereiro de 2009): 793–805. http://dx.doi.org/10.1175/2008jcli2210.1.

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Abstract The interest in climate prediction has seen a rise in the number of modeling alternatives in recent years. One way to reduce the predictive uncertainty from any such modeling procedure is to combine or average the modeled outputs. Multiple model results can be combined such that the combination weights may either be static or vary over time. This research develops a methodology for combining forecasts from multiple models in a dynamic setting. The authors mix models on a pairwise basis using importance weights that vary in time, reflecting the persistence of individual model skills. Such an approach is referred to here as a dynamic pairwise combination tree and is presented as an improvement over the case where the importance weights are static or constant over time. The pairwise importance weight is modeled as a product of a “mixture ratio” and a “bias direction,” the former representing the fraction of the absolute residual error associated with each of the paired models, and the latter representing an indicator of the sign of the two residual errors. The mixture ratio is modeled using a generalized autoregressive model and the bias direction using ordered logistic regression. The method is applied to combine three climate models, the variables of interest being the monthly sea surface temperature anomalies averaged over the Niño-3.4 region from 1956 to 2001. The authors test the combined model skill using a “leave ± 6 months out cross-validation” approach along with validation in 10-yr blocks. This study attained a small but consistent improvement of the predictive skill of the dynamically combined models compared to the existing practice of static weight combination.

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Jiang, Zongcai, e Yan Wang. "Multiattribute Group Decision Making with Unknown Decision Expert Weights Information in the Framework of Interval Intuitionistic Trapezoidal Fuzzy Numbers". Mathematical Problems in Engineering 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/635476.

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The aim of this paper is to investigate an approach to multiattribute group decision making with interval intuitionistic trapezoidal fuzzy numbers, in which the decision expert weights are unknown. First, we introduce a distance measure between two interval intuitionistic trapezoidal fuzzy matrixes, and based on the distance between individual matrix and extreme matrix, as well as the average matrix, we obtain the decision expert weights. Second, we utilize the interval intuitionistic trapezoidal fuzzy weighted geometric (IITFWG) operator and the interval intuitionistic trapezoidal fuzzy ordered weighted geometric (IITFOWG) operator to aggregate all individual interval intuitionistic trapezoidal fuzzy decision matrices into a collective interval intuitionistic trapezoidal fuzzy decision matrix and then derive the group overall evaluation values of the given alternatives. Finally, an illustrative example of emergency alternatives selection is given to demonstrate the effectiveness and superiority of the proposed method.

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Sanei, Masoud, e Shokoofeh Banihashemi. "Selecting the Best of Portfolio Using OWA Operator Weights in Cross Efficiency-Evaluation". ISRN Applied Mathematics 2014 (19 de março de 2014): 1–12. http://dx.doi.org/10.1155/2014/978314.

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The present study is an attempt toward evaluating the performance of portfolios and asset selection using cross-efficiency evaluation. Cross-efficiency evaluation is an effective way of ranking decision making units (DMUs) in data envelopment analysis (DEA). The most widely used approach is to evaluate the efficiencies in each row or column in the cross-efficiency matrix with equal weights into an average cross-efficiency score for each DMU and consider it as the overall performance measurement of the DMU. This paper focuses on the evaluation process of the efficiencies in the cross-efficiency matrix and proposes the use of ordered weighted averaging (OWA) operator weights for cross-efficiency evaluation. The OWA operator weights are generated by the minimax disparity approach and allow the decision maker (DM) or investor to select the best assets that are characterized by an orness degree. The problem consists of choosing an optimal set of assets in order to minimize the risk and maximize return. This method is illustrated by application in mutual funds and weights are obtained via OWA operator for making the best portfolio. The finding could be used for constructing the best portfolio in stock companies, in various finance organization, and public and private sector companies.

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Uriarte Adrián, José Jesús, Wenseslao Plata Rocha, Rosendo Romero Andrade, Gabriela Corrales Barraza, José C. Beltrán González e Ricardo Remond Noa. "Detection of desirable areas for urban growth through GIS and OWA: the case of Culiacan and Navolato". CIENCIA ergo sum 27, n.º 2 (16 de junho de 2020): e85. http://dx.doi.org/10.30878/ces.v27n2a6.

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Due to an accelerated growth of artificial surfaces, an increasing interest in the changes on land use has been detected in the last decade, making it necessary to propose models able to create plans of optimal and sustainable development. The goal of this work is to identify the potentially most suitable spaces for urban growth, through geospatial simulations which integrate the Geographic Information Systems and OWA (Ordered Weighted Average). We propose a sensitivity analysis methodology to the results in order to assess their robustness with respect to the input values’ weights variability, based on histograms and distances classification. Finally, the selection proposal shows a considerable percentage according to the planned area.

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Chiew, Mitchell, e Sergii Strelchuk. "Discovering optimal fermion-qubit mappings through algorithmic enumeration". Quantum 7 (18 de outubro de 2023): 1145. http://dx.doi.org/10.22331/q-2023-10-18-1145.

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Simulating fermionic systems on a quantum computer requires a high-performing mapping of fermionic states to qubits. A characteristic of an efficient mapping is its ability to translate local fermionic interactions into local qubit interactions, leading to easy-to-simulate qubit Hamiltonians.All fermion-qubit mappings must use a numbering scheme for the fermionic modes in order for translation to qubit operations. We make a distinction between the unordered labelling of fermions and the ordered labelling of the qubits. This separation shines light on a new way to design fermion-qubit mappings by making use of the enumeration scheme for the fermionic modes. The purpose of this paper is to demonstrate that this concept permits notions of fermion-qubit mappings that are optimal with regard to any cost function one might choose. Our main example is the minimisation of the average number of Pauli matrices in the Jordan-Wigner transformations of Hamiltonians for fermions interacting in square lattice arrangements. In choosing the best ordering of fermionic modes for the Jordan-Wigner transformation, and unlike other popular modifications, our prescription does not cost additional resources such as ancilla qubits.We demonstrate how Mitchison and Durbin's enumeration pattern minimises the average Pauli weight of Jordan-Wigner transformations of systems interacting in square lattices. This leads to qubit Hamiltonians consisting of terms with average Pauli weights 13.9% shorter than previously known. By adding only two ancilla qubits we introduce a new class of fermion-qubit mappings, and reduce the average Pauli weight of Hamiltonian terms by 37.9% compared to previous methods. For n-mode fermionic systems in cellular arrangements, we find enumeration patterns which result in n1/4 improvement in average Pauli weight over naïve schemes.

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Saltos Atiencia, Ramiro, e Richard Weber. "Rough-Fuzzy Support Vector Clustering with OWA Operators". Inteligencia Artificial 25, n.º 69 (21 de março de 2022): 42–56. http://dx.doi.org/10.4114/intartif.vol25iss69pp42-56.

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Rough-Fuzzy Support Vector Clustering (RFSVC) is a novel soft computing derivative of the classical Support Vector Clustering (SVC) algorithm, which has been used already in many real-world applications. RFSVC’s strengths are its ability to handle arbitrary cluster shapes, identify the number of clusters, and e?ectively detect outliers by the means of membership degrees. However, its current version uses only the closest support vector of each cluster to calculate outliers’ membership degrees, neglecting important information that remaining support vectors can contribute. We present a novel approach based on the ordered weighted average (OWA) operator that aggregates information from all cluster representatives when computing ?nal membership degrees and at the same time allows a better interpretation of the cluster structures found. Particularly, we propose the induced OWA using weights determined by the employed kernel function. The computational experiments show that our approach outperforms the current version of RFSVC as well as alternative techniques ?xing the weights of the OWA operator while maintaining the level of interpretability of membership degrees for detecting outliers.

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Chalak, Karim. "INSTRUMENTAL VARIABLES METHODS WITH HETEROGENEITY AND MISMEASURED INSTRUMENTS". Econometric Theory 33, n.º 1 (15 de fevereiro de 2016): 69–104. http://dx.doi.org/10.1017/s0266466615000390.

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We study the consequences of substituting an error-laden proxy W for an instrument Z on the interpretation of Wald, local instrumental variable (LIV), and instrumental variable (IV) estimands in an ordered discrete choice structural system with heterogeneity. A proxy W need only satisfy an exclusion restriction and that the treatment and outcome are mean independent from W given Z. Unlike Z, W need not satisfy monotonicity and may, under particular specifications, fail exogeneity. For example, W could code Z with error, with missing observations, or coarsely. We show that Wald, LIV, and IV estimands using W identify weighted averages of local or marginal treatment effects (LATEs or MTEs). We study a necessary and sufficient condition for nonnegative weights. Further, we study a condition under which the Wald or LIV estimand using W identifies the same LATE or MTE that would have been recovered had Z been observed. For example, this holds for binary Z and therefore the Wald estimand using W identifies the same “average causal response,” or LATE for binary treatment, that would have been recovered using Z. Also, under this condition, LIV using W can be used to identify MTE and average treatment effects for e.g., the population, treated, and untreated.

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Kamiohkawa, Shota, Atsushi Maruyama, Inocencio Buot e Merites Buot. "Index Assessment of Household Social Vulnerability to Climate Change: A Case Study of Laguna Province, Philippines". Journal of Environmental Science and Management 24, n.º 1 (30 de junho de 2021): 68–76. http://dx.doi.org/10.47125/jesam/2021_1/07.

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This study empirically investigated the social vulnerability of two municipalities of Laguna Province, Philippines, on the impacts of natural disasters associated with climate change. Data were obtained from interviews with seventeen experts and surveys for thirty-seven households conducted in the two municipalities. The results of the index analysis, using the weight average method and ordered probit regression, can be summarized as follows: First, the characteristics of low educational attainment, low labor rate and lack of economic resources were crucial in determining the social vulnerability class of households. Second, the social vulnerability index is determined by multiple factors, and therefore, it should not be assessed by a single variable. Third, the weights for components of the vulnerability index were insignificantly affected by geographical features and the speciality and personal traits of the experts. This suggests that local governments should develop an information system that identifies socially vulnerable households and that this should be utilized to provide the residents with education about climate change and strategies for households to reduce their potential risks from severe climatic events.

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Khameneh, Azadeh, e Adem Kiliçman. "m-Polar Fuzzy Soft Weighted Aggregation Operators and Their Applications in Group Decision-Making". Symmetry 10, n.º 11 (13 de novembro de 2018): 636. http://dx.doi.org/10.3390/sym10110636.

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Aggregation operators are important tools for solving multi-attribute group decision-making (MAGDM) problems. The main challenging issue for aggregating data in a MAGDM problem is how to develop a symmetric aggregation operator expressing the decision makers’ behavior. In the literature, there are some methods dealing with this difficulty; however, they lack an effective approach for multi-polar inputs. In this study, a new aggregation operator for m-polar fuzzy soft sets (M-pFSMWM) reflecting different agreement scenarios within a group is presented to proceed MAGDM problems in which both attributes and experts have different weights. Moreover, some desirable properties of M-pFSMWM operator, such as idempotency, monotonicity, and commutativity (symmetric), that means being invariant under any permutation of the input arguments, are studied. Further, m-polar fuzzy soft induced ordered weighted average (M-pFSIOWA) operator and m-polar fuzzy soft induced ordered weighted geometric (M-pFSIOWG) operator, which are extensions of IOWA and IOWG operators, respectively, are developed. Two algorithms are also designed based on the proposed operators to find the final solution in MAGDM problems with weighted multi-polar fuzzy soft information. Finally, the efficiency of the proposed methods is illustrated by some numerical examples. The characteristic comparison of the proposed aggregation operators shows the M-pFSMWM operator is more adaptable for solving MAGDM problems in which different cases of agreement affect the final outcome.

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Cao, Chengdong, Shouzhen Zeng e Dandan Luo. "A Single-Valued Neutrosophic Linguistic Combined Weighted Distance Measure and Its Application in Multiple-Attribute Group Decision-Making". Symmetry 11, n.º 2 (21 de fevereiro de 2019): 275. http://dx.doi.org/10.3390/sym11020275.

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The aim of this paper is to present a multiple-attribute group decision-making (MAGDM) framework based on a new single-valued neutrosophic linguistic (SVNL) distance measure. By unifying the idea of the weighted average and ordered weighted averaging into a single-valued neutrosophic linguistic distance, we first developed a new SVNL weighted distance measure, namely a SVNL combined and weighted distance (SVNLCWD) measure. The focal characteristics of the devised SVNLCWD are its ability to combine both the decision-makers’ attitudes toward the importance, as well as the weights, of the arguments. Various desirable properties and families of the developed SVNLCWD were contemplated. Moreover, a MAGDM approach based on the SVNLCWD was formulated. Lastly, a real numerical example concerning a low-carbon supplier selection problem was used to describe the superiority and feasibility of the developed approach.

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Hu, Jun, Jie Wu e Mengzhe Wang. "Research on VIKOR group decision making using WOWA operator based on interval Pythagorean triangular fuzzy numbers". AIMS Mathematics 8, n.º 11 (2023): 26237–59. http://dx.doi.org/10.3934/math.20231338.

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<abstract> <p>A new decision-making method based on interval Pythagorean triangular fuzzy numbers is proposed for fuzzy information decision-making problems, taking the advantages of interval Pythagorean fuzzy numbers and triangular fuzzy numbers into account. The VIse Kriterijumski Optimizacioni Racun (VIKOR) group decision-making method is based on the Weighted Ordered Weighted Average (WOWA) operator of interval Pythagorean triangular fuzzy numbers (IVPTFWOWA). First, this article provides the definition of the IVPTFWOWA operator and proves its degeneracy, idempotence, monotonicity, and boundedness. Second, the decision steps of the VIKOR decision method using the IVPTFWOWA operator are presented. Finally, the scientificity and effectiveness of the proposed method were verified through case studies and comparative discussions. The research results indicate that the following: (1) the IVPTFWOWA operator combines interval Pythagorean fuzzy numbers and triangular fuzzy numbers, complementing the shortcomings of the two fuzzy numbers, and can characterize fuzzy information on continuous geometry, thereby reducing decision errors caused by inaccurate and fuzzy information; (2) the VIKOR decision-making method based on the IVPTFWOWA operator applies comprehensive weights, fully considering the positional weights of the scheme attributes and the weights of raters, and fully utilizing the attribute features of decision-makers and cases; and (3) compared to other methods, there is a significant gap between the decision results obtained using this method, making it easier to identify the optimal solution.</p> </abstract>

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Wu, Yunna, Lei Qin, Chuanbo Xu e Shaoyu Ji. "Site Selection of Waste-to-Energy (WtE) Plant considering Public Satisfaction by an Extended VIKOR Method". Mathematical Problems in Engineering 2018 (8 de novembro de 2018): 1–17. http://dx.doi.org/10.1155/2018/5213504.

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Site selection of waste-to-energy (WtE) plant is critically important in the whole life cycle. Some research has been launched in the WtE plant site selection, but there is still a serious problem called Not In My Back Yard (NIMBY) effect that needs to be solved. To solve the problem, an improved multigroup VIKOR method is proposed to choose the optimal site and compromised sites. In the proposed method, the public satisfaction is fully considered where the public is invited as an evaluation group far more than creating general indicators to represent the public acceptance. First of all, an elaborate criteria system is built to evaluate site options comprehensively and the weights of criteria are identified by Analytic Hierarchy Process (AHP) method. Then, the interval 2-tuple linguistic information is adopted to assess the ratings for the established criteria. The interval 2-tuple linguistic ordered weighted averaging (ITL-OWA) operator is utilized to aggregate the opinions of evaluation committee while the opinions of the public are aggregated using weighted average operator. Finally, a case from south China which shows the computational procedure and the effectiveness of the proposed method is proved. Last but not least, a sensitivity analysis is conducted by comparing the results with different weights of evaluation group assessments.

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Zhang, Pengdan, Qing Liu e Bingyi Kang. "An improved OWA-Fuzzy AHP decision model for multi-attribute decision making problem". Journal of Intelligent & Fuzzy Systems 40, n.º 5 (22 de abril de 2021): 9655–68. http://dx.doi.org/10.3233/jifs-202168.

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Multi-attribute decision-making (MADM) is an important part of modern decision-making science. Fuzzy Analytic Hierarchy Process (Fuzzy AHP) is a popular model to deal with the issue of MADM for its flexible and effective advantages. However, The traditional Fuzzy AHP with some limitations does not consider the preference (attitude) of decision makers (DMs). In addition, some ideas of combining Ordered Weighted Average (OWA) and Fuzzy AHP don’t investigated the MADM well. Some programs are only applicable to a few examples, and more general cases do not result in effective decision making. Considering these shortcomings, an OWA-Fuzzy AHP decision model using OWA weights and Fuzzy AHP is proposed in this paper. Our contribution is that the proposed method can handle situations where the degree of fuzzy synthesis is not intersected. Moreover, the loss of information can be reduced in the process of applying the proposed method, so that the decision result is more reasonable than the previous methods. Several examples and comparative experimental simulation are given to illustrate the effectiveness and superiority of the proposed model.

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Chang, Kuei-Hu. "A Novel Enhanced Supplier Selection Method Used for Handling Hesitant Fuzzy Linguistic Information". Mathematical Problems in Engineering 2022 (23 de abril de 2022): 1–9. http://dx.doi.org/10.1155/2022/6621236.

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Today’s competitive businesses have been shifted from the company-to-company competition model to the supply chain-to-supply chain competition model. The selection of the most suitable supplier determines customer satisfaction and enterprise competitive advantage. However, the typical supplier selection approaches did not consider the ordered weights between the evaluations of attribute values, resulting in distorted assessment result. Moreover, experts often uncertainly decide the exact value of the evaluation attribute’s rating, have linguistic term sets equivocation, or give ambiguous information, which increase the difficulty of the supplier evaluation process. To deal with the aforementioned problem, we have proposed a novel enhanced supplier selection method for handling hesitant fuzzy linguistic information. To verify the approach, by taking network security system assessment as an example to explain the use of the proposed novel enhanced supplier selection method, the calculation result is compared with the result of the arithmetic average and symbolic methods. The results show that the proposed novel enhanced supplier selection method is more accurate and reasonable and can better reflect real situations.

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León-Castro, Ernesto, Luis F. Espinoza-Audelo, José M. Merigó, Anna M. Gil-Lafuente e Ronald R. Yager. "The ordered weighted average inflation". Journal of Intelligent & Fuzzy Systems 38, n.º 2 (6 de fevereiro de 2020): 1901–13. http://dx.doi.org/10.3233/jifs-190442.

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Vluymans, Sarah, Neil Mac Parthaláin, Chris Cornelis e Yvan Saeys. "Weight selection strategies for ordered weighted average based fuzzy rough sets". Information Sciences 501 (outubro de 2019): 155–71. http://dx.doi.org/10.1016/j.ins.2019.05.085.

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Zhou, Zhongkai, David L. Topping, Matthew K. Morell e Anthony R. Bird. "Changes in starch physical characteristics following digestion of foods in the human small intestine". British Journal of Nutrition 104, n.º 4 (23 de abril de 2010): 573–81. http://dx.doi.org/10.1017/s0007114510000875.

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Factors controlling the concentration of resistant starch (RS) in foods are of considerable interest on account of the potential for this type of fibre to deliver health benefits to consumers. The present study was aimed at establishing changes in starch granule morphology as a result of human small-intestinal digestion. Volunteers with ileostomy consumed six selected foods: breakfast cereal (muesli), white bread, oven-baked French fries, canned mixed beans and a custard containing either a low-amylose maize starch (LAMS) or a high-amylose maize starch (HAMS). Analysis showed that digesta total RS (as a fraction of ingested starch) was: muesli, 8·9 %; bread, 4·8 %; fries, 4·2 %; bean mix, 35·9 %; LAMS custard, 4·0 %; HAMS custard, 29·1 %. Chromatographic analysis showed that undigested food contained three major starch fractions. These had average molecular weights (MW) of 43 500 kDa, 420 kDa and 8·5 kDa and were rich in amylopectin, higher-MW amylose and low-MW amylose, respectively. The low-MW amylose fraction became enriched preferentially in the stomal effluent while the medium-MW starch fraction showed the greatest loss. Fourier transform IR spectroscopy showed that absorbance at 1022 per cm decreased after digestion while the absorbance band at 1047 per cm became greater. Such changes have been suggested to indicate shifts from less ordered to more ordered granule structures. Further analysis of amylose composition by scanning iodine spectra indicated that the MW of amylose in ileal digesta was lower than that of undigested amylose. It appears that high-MW amylose is preferentially digested and that MW, rather than amylose content alone, is associated with resistance of starch to digestion in the upper gut of humans.

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Khakzad, Hamid. "OWA operators with different Orness levels for sediment management alternative selection problem". Water Supply 20, n.º 1 (18 de outubro de 2019): 173–85. http://dx.doi.org/10.2166/ws.2019.149.

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Abstract The importance of reservoir sedimentation management as a multi criteria problem in practice with multiple decision makers is evident when one considers that the cost of replacing storage lost annually due to sediment deposition throughout the world is in the order of US$13 billion. If sedimentation can be managed successfully, as it has been in some reservoirs, the loss in reservoir storage space due to this phenomenon can be lowered significantly. The purpose of this research is to develop the ordered weighted averaging (OWA) algorithm and apply it and to select the most preferred alternative with different Orness levels for sediment management in dam reservoirs to satisfy the technical and executive requirements, economic factors, social welfare, and environmental impacts. In this way, we present analytic forms of OWA operator weighting functions, each of which has properties of rank-based weights and a constant level of Orness, irrespective of the number of objectives considered. The model are successfully applied to the Dez hydropower reservoir, which has faced serious sedimentation problems. Results of this study provide a general class of parameterized aggregation operators that include the min, max, and average and have shown themselves to be useful for modeling many different kinds of aggregation problems.

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Kohler, Stefan, Norman Sitali e Nicolas Paul. "A Framework for Assessing Import Costs of Medical Supplies and Results for a Tuberculosis Program in Karakalpakstan, Uzbekistan". Health Data Science 2021 (26 de agosto de 2021): 1–13. http://dx.doi.org/10.34133/2021/9813732.

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Background. Import of medical supplies is common, but limited knowledge about import costs and their structure introduces uncertainty to budget planning, cost management, and cost-effectiveness analysis of health programs. We aimed to estimate the import costs of a tuberculosis (TB) program in Uzbekistan, including the import costs of specific imported items. Methods. We developed a framework that applies costing and cost accounting to import costs. First, transport costs, customs-related costs, cargo weight, unit weights, and quantities ordered were gathered for a major shipment of medical supplies from the Médecins Sans Frontières (MSF) Procurement Unit in Amsterdam, the Netherlands, to a TB program in Karakalpakstan, Uzbekistan, in 2016. Second, air freight, land freight, and customs clearance cost totals were estimated. Third, total import costs were allocated to different cargos (standard, cool, and frozen), items (e.g., TB drugs), and units (e.g., one tablet) based on imported weight and quantity. Data sources were order invoices, waybills, the local MSF logistics department, and an MSF standard product list. Results. The shipment contained 1.8 million units of 85 medical items of standard, cool, and frozen cargo. The average import cost for the TB program was 9.0% of the shipment value. Import cost varied substantially between cargos (8.9–28% of the cargo value) and items (interquartile range 4.5–35% of the item value). The largest portion of the total import cost was caused by transport (82–99% of the cargo import cost) and allocated based on imported weight. Ten (14%) of the 69 items imported as standard cargo were associated with 85% of the standard cargo import cost. Standard cargo items could be grouped based on contributing to import costs predominantly through unit weight (e.g., fluids), imported quantity (e.g., tablets), or the combination of unit weight and imported quantity (e.g., items in powder form). Conclusion. The cost of importing medical supplies to a TB program in Karakalpakstan, Uzbekistan, was sizable, variable, and driven by a subset of imported items. The framework used to measure and account import costs can be adapted to other health programs.

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Leon-Castro, Ernesto, Fabio Blanco-Mesa, Alma Montserrat Romero-Serrano e Marlenne Velázquez-Cazares. "The Ordered Weighted Average Human Development Index". Axioms 10, n.º 2 (7 de maio de 2021): 87. http://dx.doi.org/10.3390/axioms10020087.

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The main aim is to propose a new method for estimating the Human Development Index using ordered weighted average. To develop this method, ordered weighted geometric average (OWGA), induced OWGA prioritized OWA (POWA) operator are studied. Using Human Development Index formulation in combination to aggregations operators presented above is proposed the prioritized induced ordered weighted geometric average (PIOWGA) operator. A mathematical application is carried out to estimate the Human Development Index and compare it with the traditional method and other existing methods. Finally, it is noted that decision makers have an influence on the order given in the ranking by its attitude and criterion, and method can capture the subjective information prioritized by them.

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Ruda, Aleš. "CARTOGRAPHIC VISUALIZATION OF OUTPUTS FOR SPATIAL DECISION-MAKING IN REGIONAL DEVELOPMENT". Geodesy and Cartography 41, n.º 4 (17 de dezembro de 2015): 174–84. http://dx.doi.org/10.3846/20296991.2015.1120431.

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Regional development is full of planning and decision making. Having precise results for spatial decision making (SDM) is more than necessary. On one site, there are many approaches how to process input data, on the other hand thematic cartography also operates with many visualizing methods and techniques. Loss of accuracy of the results is more than expected because there are two phases (data processing during SDM and cartographic visualization) where the accuracy might be distorted. In both phases processing recommendations must be obeyed. Selection of spatial decision making method must follow considered aims as well as visualization techniques and setting their parameters (especially during reclassification, interpolation or generalization). Paper deals with the proposal of elementary scheme of SDM and related visualization during two case studies (CS). First CS represents composite indicators proposal followed by weighted sum method using heuristics approaches with the aim to identify the tourism influence on the landscape. Combined visualization techniques for quantitative and qualitative data are presented. Second CS uses ordered weighted average method for finding the best place for building of a new public logistics centre. Constraints and factors represent key indicators and following factor and order weights enable to propose the best accepted risk model. In this case grid maps describe derived values and chosen reclassification documents conversion into linguistic variables.

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Samani, Zeinab Neisani, Ali Asghar Alesheikh, Mohammad Karimi, Najmeh Neysani Samany, Sayeh Bayat, Aynaz Lotfata e Chiara Garau. "Advancing Urban Healthcare Equity Analysis: Integrating Public Participation GIS with Fuzzy Best–Worst Decision-Making". Sustainability 16, n.º 5 (20 de fevereiro de 2024): 1745. http://dx.doi.org/10.3390/su16051745.

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This study provides an innovative collaborative spatial decision support system (SDSS) that aims to ensure an equitable spatial distribution of healthcare services. Evaluating the equality of access to health services across different geographical areas is important, as it requires the analysis of various criteria such as the proximity of health centres and hospitals (HCHs), the quality of services offered, connectivity to primary roads, the availability of public transportation hubs, and the density and distribution patterns of HCHs. This purpose is accomplished via the use of geographic information systems (GIS) and multi-criteria decision analysis (MCDA) methods. The proposed model includes the weights of the criteria, which are determined through the ordered weighted average (OWA) and evaluated based on their ORness, which ranges from 0 to 1. Furthermore, this model is improved by the best–worst fuzzy method (F-BWM). This approach produces a spatial map that clearly shows the equity of healthcare systems in urban environments. The findings show that the maximum score observed in this study was 0.38% (with an ORness value of 1), whilst the minimum score recorded was 0.28%. In the most severe scenario (ORness = 0), over 70% of the region shows different degrees of fairness, ranging from moderate to suitable and very suitable conditions. Governments and health authorities can use this information strategically to allocate resources and address inequities in access to healthcare facilities.

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Papageorgiou, Konstantinos, Pramod K. Singh, Elpiniki Papageorgiou, Harpalsinh Chudasama, Dionysis Bochtis e George Stamoulis. "Fuzzy Cognitive Map-Based Sustainable Socio-Economic Development Planning for Rural Communities". Sustainability 12, n.º 1 (30 de dezembro de 2019): 305. http://dx.doi.org/10.3390/su12010305.

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Every development and production process needs to operate within a circular economy to keep the human being within a safe limit of the planetary boundary. Policymakers are in the quest of a powerful and easy-to-use tool for representing the perceived causal structure of a complex system that could help them choose and develop the right strategies. In this context, fuzzy cognitive maps (FCMs) can serve as a soft computing method for modelling human knowledge and developing quantitative dynamic models. FCM-based modelling includes the aggregation of knowledge from a variety of sources involving multiple stakeholders, thus offering a more reliable final model. The average aggregation method for weighted interconnections among concepts is widely used in FCM modelling. In this research, we applied the OWA (ordered weighted averaging) learning operators in aggregating FCM weights, assigned by various participants/ stakeholders. Our case study involves a complex phenomenon of poverty eradication and socio-economic development strategies in rural areas under the DAY-NRLM (Deendayal Antyodaya Yojana-National Rural Livelihoods Mission) in India. Various scenarios examining the economic sustainability and livelihood diversification of poor women in rural areas were performed using the FCM-based simulation process implemented by the “FCMWizard” tool. The objective of this study was three-fold: (i) to perform a brief comparative analysis between the proposed aggregation method called “OWA learning aggregation” and the conventional average aggregation method, (ii) to identify the significant concepts and their impact on the examined FCM model regarding poverty alleviation, and (iii) to advance the knowledge of circular economy in the context of poverty alleviation. Overall, the proposed method can support policymakers in eliciting accurate outcomes of proposed policies that deal with social resilience and sustainable socio-economic development strategies.

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Blanco-Mesa, Fabio, Ernesto León-Castro, José M. Merigó e Zeshui Xu. "Bonferroni means with induced ordered weighted average operators". International Journal of Intelligent Systems 34, n.º 1 (4 de outubro de 2018): 3–23. http://dx.doi.org/10.1002/int.22033.

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Liu, Ping, Jiao Xue, Shisheng Tong, Wenxia Dong e Peipei Wu. "Structure Characterization and Hypoglycaemic Activities of Two Polysaccharides from Inonotus obliquus". Molecules 23, n.º 8 (4 de agosto de 2018): 1948. http://dx.doi.org/10.3390/molecules23081948.

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In the present study, two polysaccharides (HIOP1-S and HIOP2-S) were isolated and purified from Inonotus obliquus using DEAE-52 cellulose and Sephadex G-100 column chromatography. The structural characterization and in vitro and in vivo hypoglycaemic activities of these molecules were investigated. HPLC analysis HIOP1-S was a heterpolysaccharide with glucose and galactose as the main compontent monosaccharides (50.247%, molar percentages). However, HIOP2-S was a heterpolysaccharide with glucose as the main monosaccharide (49.881%, molar percentages). The average molecular weights of HIOP1-S and HIOP2-S were 13.6 KDa and 15.2 KDa, respectively. The β-type glycosidic bond in HIOP1-S and HIOP2-S was determined using infrared analysis. 1H-NMR spectra indicated that HIOP2-S contains the β-configuration glycosidic bond, and the glycoside bonds of HIOP1-S are both α-type and β-type. The ultraviolet scanning showed that both HIOP1-S and HIOP2-S contained a certain amount of binding protein. Congo red test showed that HIOP1-S and HIOP2-S could form a regular ordered triple helix structure in the neutral and weakly alkaline range. HIOP1-S and HIOP2-S showed strong α-glucosidase inhibitory activities and increased the glucose consumption of HepG2 cells. In addition, Streptozotocin (STZ)-induced hyperglycaemic mice were used to evaluate the antihyperglycaemic effects of HIOP1-S and HIOP2-S in vivo. The results showed that HIOP2-S had antihyperglycaemic effects. Taken together, these results suggest that HIOP1-S and HIOP2-S have potential anti-diabetic effects.

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Maldonado, Sebastián, José Merigó e Jaime Miranda. "Redefining support vector machines with the ordered weighted average". Knowledge-Based Systems 148 (maio de 2018): 41–46. http://dx.doi.org/10.1016/j.knosys.2018.02.025.

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Fernández, Elena, Miguel A. Pozo, Justo Puerto e Andrea Scozzari. "Ordered Weighted Average optimization in Multiobjective Spanning Tree Problem". European Journal of Operational Research 260, n.º 3 (agosto de 2017): 886–903. http://dx.doi.org/10.1016/j.ejor.2016.10.016.

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Laengle, Sigifredo, Gino Loyola e Jose M. Merigo. "Mean-Variance Portfolio Selection With the Ordered Weighted Average". IEEE Transactions on Fuzzy Systems 25, n.º 2 (abril de 2017): 350–62. http://dx.doi.org/10.1109/tfuzz.2016.2578345.

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Fernández, Elena, Miguel A. Pozo e Justo Puerto. "Ordered weighted average combinatorial optimization: Formulations and their properties". Discrete Applied Mathematics 169 (maio de 2014): 97–118. http://dx.doi.org/10.1016/j.dam.2014.01.001.

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Linares-Mustarós, Salvador, Joan C. Ferrer-Comalat, Dolors Corominas-Coll e José M. Merigó. "The ordered weighted average in the theory of expertons". International Journal of Intelligent Systems 34, n.º 3 (2 de novembro de 2018): 345–65. http://dx.doi.org/10.1002/int.22055.

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Shouzhen, Zeng, Wang Qifeng, José Merigó e Pan Tiejun. "Induced intuitionistic fuzzy ordered weighted averaging: Weighted average operator and its application to business decision-making". Computer Science and Information Systems 11, n.º 2 (2014): 839–57. http://dx.doi.org/10.2298/csis130109046s.

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We present the induced intuitionistic fuzzy ordered weighted averaging-weighted average (I-IFOWAWA) operator. It is a new aggregation operator that uses the intuitionistic fuzzy weighted average (IFWA) and the induced intuitionistic fuzzy ordered weighted averaging (I-IFOWA) operator in the same formulation. We study some of its main properties and we have seen that it has a lot of particular cases such as the IFWA and the intuitionistic fuzzy ordered weighted averaging (IFOWA) operator. We also study its applicability in a decision-making problem concerning strategic selection of investments. We see that depending on the particular type of I-IFOWAWA operator used, the results may lead to different decisions.

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Blanco‐Mesa, Fabio, Ernesto León‐Castro, José M. Merigó e Enrique Herrera‐Viedma. "Variances with Bonferroni means and ordered weighted averages". International Journal of Intelligent Systems 34, n.º 11 (26 de agosto de 2019): 3020–45. http://dx.doi.org/10.1002/int.22184.

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