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The assessment of a theory is the main objective of scientists. Theories are always introduced by models, and model selection is applied to many various fields of scientific studies in order to corroborate or verify the theory as the winning one among a set of competing hypotheses. Different criteria are taken as bases to select one model among several parallel models in both statistical and visual types. This paper proposes a new method in model selection based on the solutions of a fuzzy decision-making problem. The method enables us to apply systematically all desired validation criteria by defining a proper possibility distribution function (PDF) for each criterion. The generality of the method allows us to consider even intuitive, inaccurate, or linguistic criteria. Finally, the maximization of a utility function, rationally composed of the PDFs, will determine the best choice of competing models. The method is illustrated by two sets of linear and nonlinear parallel models. Index Terms--Fuzzy decision making (FDM), model selection, model validation, multicriteria model selection.

Energy plays a key role in sustainable development. Formulation of an energy model will help in the proper allocation of available energy resources. The objective of this article is to allocate optimally to each end user a certain amount of energy to be supplied by a given resource in Iran to reduce greenhouse gases. For this purpose, energy demands of end users are forecasted, and the outcomes are used in a fuzzy linear programming model, which determines the best allocation of energy resources in Iran from 2012 to 2020. The result shows a large portion of crude oil and natural gas will be allocated for exports. Transportation sector will be the major consumer of the petroleum products. Higher amounts of natural gas compared with the petroleum products will be allocated to power plants. Moreover, a considerable portion of natural gas should be injected into the oil reservoirs. These analyses would provide scientific basis for the optimal allocation of energy resources in meeting the future energy demand in Iran. © 2012 American Institute of Chemical Engineers Environ Prog, 32: 854-859, 2013 [ABSTRACT FROM AUTHOR]

As far as the electricity market is considered, both governments and private sector are interested in energy supply industry and so consider it essential to predict energy demand. Solution of the problem depends on availability of a model. This paper proposes a systematically developed model. It is based on a previously performed exogeneity investigation of various quantified variables. A certain nonlinear model among a collection of 100 models with different inputs is chosen as the most appropriate model. Structure of all nonlinear competing models is established according to logical conjunctive and disjunctive relationships between variables. Different combinations of the exogenous variables generate these models. At first, unacceptable models are put away applying coefficient sign significance criterion and error validity. An automated fuzzy decision-making process determines the winner model, which is a hybrid nonlinear model, among the other remaining models. [ABSTRACT FROM AUTHOR]