We lived in uncertain word and prediction in this uncertain word is a major issue. Prediction in cricket is very complex because there are many factors which are effecting on results. Weather, pitch, Conditions, Home grounds are some of these factors. In this article it is aimed to predict the results of PSL-2020 by using TOPSIS and Fuzzy TOPSIS methods. It will be interesting because first time in PSL history it is going to be held in Pakistan. But we use some serious factor to predict the winner of PSL-2020.

The purpose of this study was to evaluate the environmental risks of Alborz Dam on Bababrood River in Babol city, using multi-criteria decision making methods. Initially, environmental identification of the study area was carried out, Then a list of environmental risks identified in the construction and exploitation phase was prepared and presented to environmental experts familiar with the Alborz dam area in the form of a questionnaire. environmental risks scored by environmental experts based on three indicators, Severity of occurrence, Probability of occurrence, Then environmental risks ranking was performed using TOPSIS and Fuzzy TOPSIS methods. The most important risks of Alborz dam using TOPSIS method in the construction phase, respectively: Was Obtained, Destruction of forest within the dam with a score of 0. 926, Displacement of reservoir residents with a score of 0. 837 And in the phase of operation: Thermal stratification of dam reservoir with a score of 0. 847, Landslide with a score of 0. 751. Also, the most important risks of the Alborz dam using the Fuzzy Topsis method in the construction phase, respectively: Was Obtained, Displacement of reservoir residents with a score of 0. 682, Demolition of forest within the dam with a score of 0. 677, And in the phase of operation, respectively: Thermal stratification of dam reservoir with a score of 0. 645, Landslide with a score of 0. 630. Finally, one method of integration (average rating method) was used to resolve the conflict between the results.

The present paper proposes a new application of the prediction of human behavior using TOPSIS as an appropriate tool for data optimization. Our hypothesis was that the analysis of the candidates with this method was influenced by the change of their behavior. We found that the behavior change could occur in more than one time span when the behavior of two candidates changed simultaneously. One of the advantages of this study is that the pattern of the behavior change with time is predicted with this method. Another advantage is that the modifications in the TOPSIS algorithm have made the predictions independent from the need of changing the fuzzy membership degrees of the candidates. This is the first time that these modifications in this technique with a new application including the numerical analysis of cognitive date are reported. Our results can be used in cognitive science, experimental psychology, cognitive informatics and artificial intelligence.

Mineral sector as the essential part of the economy has important role for supplying industries' raw materials. Investment promotion in this sector can earn high value added to the most industries. Consequently, it is necessary to recognize high priority minerals for future investment.In this paper, TOPSIS (Technique for Order Preference by Similarity to Ideal Solution) method, one of the major techniques of multiple attribute decision making process, utilized for ranking the 33 minerals for future investment. For this purpose, based on the interviews with mining experties, 29 criteria are defined. Then their quantities and weights are calculated. After that, based on the weights obtaining from the interviews as well as applying equal weights, the rank of each mineral is determined. The results show that copper, coal, iron, gold, chromites, lead and zinc have high priority respectively for future investments in Iran.

Today, in the real world, many quantitative and qualitative factors like the quality, price, flexibility and efficiency of the delivery process should be considered in decision making problems. Therefore, linguistic variables can be expressed in trapezoidal or triangular fuzzy numbers are used to assess the rating of each alternative and the weight of each criterion. Hence, the aim of this paper is to extend the TOPSIS method to decision-making problems with fuzzy data to find appropriate alternative under vague and ambiguous environment with team of decision making. According to the concept of the TOPSIS method in group multiple criteria decision making (GMCDM) problem, an index of closeness coefficient is defined to determine the ranking order of all alternatives by calculating the distance to the both fuzzy ideal solution and fuzzy anti-ideal solution based on approach of ranking of the fuzzy numbers simultaneously. Finally, an example is given to highlight the procedure of the proposed method.

Supplier selection is one of the critical activities for firms to gain competitive advantage and achieve the objectives of the whole supply chain. In this paper based on a DEA-TOPSIS method for MADM problems a flexible strategy for supplier selection is introduced.