We compared probability surfaces derived using one set of environmental variables in three Geographic Information Systems （GIS） -based approaches： logistic regression and Akaike＇s Information Criterion （AIC）, Mu...We compared probability surfaces derived using one set of environmental variables in three Geographic Information Systems （GIS） -based approaches： logistic regression and Akaike＇s Information Criterion （AIC）, Multiple Criteria Evaluation （MCE）, and Bayesian Analysis （specifically Dempster-Shafer theory）. We used lynx Lynx canadensis as our focal species, and developed our environment relationship model using track data collected in Banff National Park, Alberta, Canada, during winters from 1997 to 2000. The accuracy of the three spatial models were compared using a contingency table method. We determined the percentage of cases in which both presence and absence points were correctly classified （overall accuracy）, the failure to predict a species where it occurred （omission error） and the prediction of presence where there was absence （commission error）. Our overall accuracy showed the logistic regression approach was the most accurate （74.51%）. The multiple criteria evaluation was intermediate （39.22%）, while the Dempster-Shafer （D-S） theory model was the poorest （29.90%）. However, omission and commission error tell us a different story： logistic regression had the lowest commission error, while D-S theory produced the lowest omission error. Our results provide evidence that habitat modellers should evaluate all three error measures when ascribing confidence in their model. We suggest that for our study area at least, the logistic regression model is optimal. However, where sample size is small or the species is very rare, it may also be useful to explore and/or use a more ecologically cautious modelling approach （e.g. Dempster-Shafer） that would over-predict, protect more sites, and thereby minimize the risk of missing critical habitat in conservation plans .展开更多
A ship＇s crew plays an important role in the maritime transportation sector and their performance is paramont in the shipping industry. On this account, an impartial evaluation of the crew＇s performance is an import...A ship＇s crew plays an important role in the maritime transportation sector and their performance is paramont in the shipping industry. On this account, an impartial evaluation of the crew＇s performance is an important issue. In this paper, the ship officer＇s performance evaluation problem is studied. The performance evaluation criteria that shipping companies take into account are determined and a performance evaluation process is modelled by using the FAHP （Fuzzy Analytic Hierarchy Process） based on Chang＇s Algorithm. Linguistic variables and fuzzy numbers are used in the assessment process. The results of the proposed model demonstrate that the FAHP method is effective and helps managers make better and more reliable decisions under fuzzy circumstances.展开更多
The Paraconsistent Many-Valued Similarity (PMVS) method for multi-attribute decision making will be incomplete as a decision model if it is not extended to the realm of group decision-making. Therefore, in this articl...The Paraconsistent Many-Valued Similarity (PMVS) method for multi-attribute decision making will be incomplete as a decision model if it is not extended to the realm of group decision-making. Therefore, in this article, our primary objective is to show how the paraconsistent many-valued similarity method can be used to solve group decision-making problems involving choice making or ranking of a finite set of decision alternatives. Moreover, since weights are very important parameters in multi-attribute decision-making, we have introduced the Borda rule to calculate the weights of experts and that of every criterion under consideration. To demonstrate how the proposed method works, a numerical example on energy sources of an economy from the points of view of a group of experts is investigated. Further, we compare the results of this new approach with that of fuzzy TOPSIS group decision-making method to illustrate the robustness and effectiveness of the former.展开更多
This paper presents a reputation evaluating model for non-govemment-run scientific research and technical service organizations of China. The model is composed of quantitative and qualitative factors, fuzzy comment se...This paper presents a reputation evaluating model for non-govemment-run scientific research and technical service organizations of China. The model is composed of quantitative and qualitative factors, fuzzy comment set and weight vector. The fuzzy judgement technique is applied in the model. The application of the model is also demonstrated in the paper.展开更多
文摘We compared probability surfaces derived using one set of environmental variables in three Geographic Information Systems （GIS） -based approaches： logistic regression and Akaike＇s Information Criterion （AIC）, Multiple Criteria Evaluation （MCE）, and Bayesian Analysis （specifically Dempster-Shafer theory）. We used lynx Lynx canadensis as our focal species, and developed our environment relationship model using track data collected in Banff National Park, Alberta, Canada, during winters from 1997 to 2000. The accuracy of the three spatial models were compared using a contingency table method. We determined the percentage of cases in which both presence and absence points were correctly classified （overall accuracy）, the failure to predict a species where it occurred （omission error） and the prediction of presence where there was absence （commission error）. Our overall accuracy showed the logistic regression approach was the most accurate （74.51%）. The multiple criteria evaluation was intermediate （39.22%）, while the Dempster-Shafer （D-S） theory model was the poorest （29.90%）. However, omission and commission error tell us a different story： logistic regression had the lowest commission error, while D-S theory produced the lowest omission error. Our results provide evidence that habitat modellers should evaluate all three error measures when ascribing confidence in their model. We suggest that for our study area at least, the logistic regression model is optimal. However, where sample size is small or the species is very rare, it may also be useful to explore and/or use a more ecologically cautious modelling approach （e.g. Dempster-Shafer） that would over-predict, protect more sites, and thereby minimize the risk of missing critical habitat in conservation plans .
文摘A ship＇s crew plays an important role in the maritime transportation sector and their performance is paramont in the shipping industry. On this account, an impartial evaluation of the crew＇s performance is an important issue. In this paper, the ship officer＇s performance evaluation problem is studied. The performance evaluation criteria that shipping companies take into account are determined and a performance evaluation process is modelled by using the FAHP （Fuzzy Analytic Hierarchy Process） based on Chang＇s Algorithm. Linguistic variables and fuzzy numbers are used in the assessment process. The results of the proposed model demonstrate that the FAHP method is effective and helps managers make better and more reliable decisions under fuzzy circumstances.
文摘The Paraconsistent Many-Valued Similarity (PMVS) method for multi-attribute decision making will be incomplete as a decision model if it is not extended to the realm of group decision-making. Therefore, in this article, our primary objective is to show how the paraconsistent many-valued similarity method can be used to solve group decision-making problems involving choice making or ranking of a finite set of decision alternatives. Moreover, since weights are very important parameters in multi-attribute decision-making, we have introduced the Borda rule to calculate the weights of experts and that of every criterion under consideration. To demonstrate how the proposed method works, a numerical example on energy sources of an economy from the points of view of a group of experts is investigated. Further, we compare the results of this new approach with that of fuzzy TOPSIS group decision-making method to illustrate the robustness and effectiveness of the former.
文摘This paper presents a reputation evaluating model for non-govemment-run scientific research and technical service organizations of China. The model is composed of quantitative and qualitative factors, fuzzy comment set and weight vector. The fuzzy judgement technique is applied in the model. The application of the model is also demonstrated in the paper.
