Any illegal attempt to not pay taxes, such as not giving the necessary information about taxable income and benefits to the authorities, is called tax evasion, and determining the level of tax evasion and having a better understanding of its reasons will help in the Process of finding mechanisms to prevent it or reduce its intensity. the purpose of this study is to prioritize effective factors on tax evasion. For this purpose, by collecting the necessary information through library method and then distribution of questionnaire in two stages, the collected data were analyzed using Fuzzy Analytic Hierarchy Process method. the statistical population studied in this study is senior managers, staff managers and active experts who have a working relationship in different units and departments of the tax administration, among which 20 were selected as samples. To determine the importance and ranking of the main factors of the main factors and effective sub-factors on tax evasion, Group Fuzzy Analytic Hierarchy Process ((GFAHP)) has been used. The results of the prioritization of research variables have shown that the the most important main factor for tax evasion is the determined executive factor and the main economic-environmental and legal factors in the next priorities.

With the availability of websites and the growth of comments, reviews of user-generated content are published on the Internet. Sentiment Classification is one of the most common problems in text mining, which applies to categorize reviews into positive and negative classes. Pre-Processing has an important role when these textual contexts are employed by machine learning techniques. Without efficient pre-Processing methods, unreliable results will be achieved. This research probes to investigate the performance of pre-Processing for the Sentiment Classification problem on three popular datasets. We suggest a high-performance framework to enhance classification performance. First, features of user's opinions are extracted based on three methods: (1) Backward Feature Selection; (2) High Correlation Filter; and (3) Low Variance Filter. Second, the error rate of the primary classification for each method is calculated through the perceptron. Finally, the best method is selected through the Fuzzy Analytic Hierarchy Process. This framework is beneficial for companies to observe people's comments about their brands and for many other applications. The current authors have provided further evidence to confirm the superiority of the proposed framework. The obtained results indicate that on average this proposed framework outperformed its counterparts. This framework yields 90. 63 precision, 90. 89 accuracy, 91. 27 recall, and 91. 05% f-measure.

Despite the fact that the energy sector has contributed to the destruction of the environment through its emissions of greenhouse gases, human societies have paid more attention to renewable energy sources such as small hydropower plants in response to this issue. For the purpose of determining zoning, 12 layers of environmental, technical, and geographical criteria have been used. In order to achieve the results of this study, we combined multi-criteria decision-making (MCDM) with Fuzzy algorithms. Basically, the Fuzzy-AHP method of weighting is used as a method for evaluating the technical and environmental criteria that do not have an internal relationship with one another. Using the Fuzzy-ANP method, we are able to weight geographical criteria that are related to one another and are evaluated in terms of their relative importance. In order to identify the zoning map, layers have been overlaid by using the gamma operator 0.9 in order to identify the zoning map. In order to produce the final zoning map, the zoning and the physiographic maps are combined using the Sum operator. Therefore, 13 suitable sites were selected for the construction of power plants, resulting in 22084.69 megawatts of energy being generated per year and 5.8 tons of greenhouse gases being prevented from being released into the atmosphere. During the course of this study, a watershed located in Iran, known as the Karoun watershed, was studied. Furthermore, the methods applied in this research could be performed in other watersheds and evaluated the potential of other power plants such as solar and wind power plants.

One of the basic stages in strategic planning is the prioritization of strategies. In this area, many researches have been made and a lot of methodologies have been presented. Although these methods try to improve the analysis situation, they lose some useful information during the decision making Process.In this article, the Fuzzy Analytic Hierarchy Process method is used for determining the importance of each strategy and sorting them. This approach is useful for saving some information which obtained from real situation. Also by using this flexible approach, decision makers are able to focus simultaneously just on two options, instead of many options. This approach is used for analyzing the traning center. For description about this approach, a numerical example is also presented.

Purpose: Neuromarketing is an interdisciplinary and emerging field which can be used in order to relate consumer behavior to neuroscience. So, in recent decades, the importance and interest in buying sustainable products for protecting the environment has been increased. Thus, the present study was done with the aim of Fuzzy Analytic Hierarchy Process of neuromarketing evaluation criteria for sustainable products. Methodology: The research was performed with a quantitative approach and by using multiple-criteria decision analysis. For this purpose, in order to gain a deep understanding of the subject and collecting useful data, after carefully reviewing the related studies, the views of 16 experts were collected using a Fuzzy hierarchical researcher-made questionnaire, which the inconsistency rate of the questionnaires confirmed reliability of them. Also, sensitivity analysis was used to ensure. Findings: The results showed that the criteria for evaluating neuromarketing are in seven categories, which based on FAHP are: accuracy, biasness, exploration of memory and emotion, information quality, usefulness, time saving, cost, respectively. Also, the alternatives of marketing for sustainable products affected by neuromarketing in order of priority are: advertising, product design and development, branding, consumer decision, pricing and distribution. Sensitivity analysis also showed that the research findings are confirmed, but in the case of two criteria of biasness and exploration of memory and emotions, there is a possibility of displacement. Originality/Value: Neuromarketing, due to the provision of high-precision and high-quality information and the reduction of bias in the analysis of results, provides the possibility of predicting consumer buying behavior and affects the marketing mix of sustainable products.

Use of new techniques to evaluate irrigation areas can enhance water use efficiency in agriculture. In this study, the Fuzzy Analytic Hierarchy Process (FAHP) was used to qualitative land suitability for sprinkler irrigation and was compared with the parametric method. Evaluation based on parametric method showed that an area of about 1597. 83 hectares (31%) of the lands was highly suitable (S1) and an area of about 787. 3 hectares (15%) was “ moderately suitable” (S2). About 2242. 9 hectares (43%) were marginally suitable (S3). Permanently inappropriate suitability included about 546. 91 hectares (11%). Inappropriate in present condition suitability matched no land in the study zone. Based on the Fuzzy Analytic Hierarchical Process, there was not highly suitable (S1) area in the plain. The parts with S2 suitability also included an area of about 432. 96 hectares (8. 3%). Moreover, areas of about 3100. 98 hectares (59. 9%) were marginally suitable (S3). Some southwest and eastern parts of the plain were not currently suitable (N1) that included an area of about 1277. 68 hectares (24. 6%). N2 suitability was also observed in some southern in two parts including an area of about 363. 38 hectares (7%). Since about 31% of the lands were included as "highly suitable" areas based on the parametric method, and in contrast, there was no "highly suitable" areas in FAHP method, so considering the area of "highly suitable" shown that there was a significant difference between the two methods in terms of "highly suitable" land evaluation. Considering the gradual changes in soil properties, FAHP evaluation has higher accuracy than the ordinary parametric method in evaluating land suitability.

To select an enterprise resource planning (ERP) system is time consuming due to the resource constraints, the software complexity, and the different of alternatives. A comprehensively systematic selection policy for ERP system is very important to the success of ERP project. In this paper, we propose a Fuzzy Analytic Hierarchy Process (FAHP) method to evaluate the alternatives of ERP system. The selection criteria of ERP system are numerous and Fuzzy, so how to select an adequate ERP system is crucial in the early phase of an ERP project. The framework decomposes ERP system selection into three main factors. The goal of this paper is to select the best alternative that meets the requirements with respect to product factors, system factors and management factors. The sub-attributes (sub-factors) related to ERP selection have been classified into twelve main categories of Functionality, Reliability, Usability, Efficiency, Maintainability, Cost, Implementation time, User friendliness, Flexibility, Vendor Reputation, Consultancy Services, and R&D Capability and arranged in a Hierarchy structure. These criteria and factors are weighted and prioritized and finally a framework is provided for ERP selection with the Fuzzy AHP method. Also, a real case study from Iran is also presented to demonstrate efficiency of this method in practice.