In multi-criteria group decision-making (MCGDM), one of the most important problems is to determine the weights of criteria and experts. This paper intends to present two Min-Max models to optimize the point estimates of the weights. Since each expert generally possesses a uniform viewpoint on the importance (weighted value) of each criterion when he/she needs to rank the alternatives, the obje...

earthworms are an important part of food chain in soil ecosystem. in polluted soils, heavy metals are consumed by earthworms and transferred to other organisms through food chain, resulting in many adverse health impacts. due to the benefits of earthworms for soil fertility, it is important to assess the effects of soil pollution on population, biomass and functions of earthworms. to determine ...

Failure modes and effects analysis (FMEA) is a well-known risk analysis approach that has been conducted to distinguish, analyze and mitigate serious failure modes. It demonstrates the effectiveness and the ability of understanding and documenting in a clear manner; however, the FMEA has weak points and it has been criticized by some authors. For example, it does not consider relative importanc...

Selecting suitable street trees is critical for avoiding these problems of trees. Resident experiences should be considered in tree selection to improve effective management because resident preferences tend differ from those managers. This study aimed explore the criteria by residents and compare between experts. implemented two studies achieve purpose. Study 1 used exploratory factor analysis...

the purpose of this study was to analyze biotechnology experts’ attitude in university centers of tehran province towards use of transgenic plants. the design of the study was descriptive, and it was carried out through a survey method. the target population consisted of biotechnology experts in university centers of tehran province (n=75). though kerjcie and morgan sample size table and ratio ...

We consider algorithms for combining advice from a set of experts. In each trial, the algorithm receives the predictions of the experts and produces its own prediction. A loss function is applied to measure the discrepancy between the predictions and actual observations. The algorithm keeps a weight for each expert. At each trial the weights are first used to help produce the prediction and the...