Abstract As an important pre-processing method in machine learning, feature selection eliminates data redundancy and reduces feature dimensions and computational time complexity effectively. In order to further reduce the number of iterations of the feature selection algorithm and improve the classification accuracy, a new hybrid feature selection algorithm is proposed, which combines the filter algorithm based on information gain and the wrapper algorithm based... As an important pre-processing method in machine learning, feature selection eliminates data redundancy and reduces feature dimensions and computational time complexity effectively. In order to further reduce the number of iterations of the feature selection algorithm and improve the classification accuracy, a new hybrid feature selection algorithm is proposed, which combines the filter algorithm based on information gain and the wrapper algorithm based on Sequential Forward Floating Search (SFFS) and Decision Tree (DT). The optimal candidate feature subset is quickly found by ranking the features using information gain. In order to avoid the nesting effect of features, SFFS algorithm is used to reduce feature dimensions of the optimal candidate feature subset. The experiments show that the maximum ratio of the number of reduced features and the number of initial features is 92.86%. Compared with other feature selection algorithms, the maximum decline of the number of iterations is about 67.8%, and the maximum increase of the classification accuracy is about 10.5%. The results prove that the hybrid algorithm possesses higher computational efficiency and classification accuracy. Read More Read Less

Abstract In this paper, we investigate the interval intuitionistic trapezoidal fuzzy multiple attribute decision making (MADM) problems in which the attributes are in different priority level. Motivated by the ideal of prioritized aggregation operators bu R.R. Yager, we developed some prioritized aggregation operators for aggregating interval intuitionistic trapezoidal fuzzy information, and then apply them to develop some models for interval intuitionistic trapezoidal fuzzy multiple attribute... In this paper, we investigate the interval intuitionistic trapezoidal fuzzy multiple attribute decision making (MADM) problems in which the attributes are in different priority level. Motivated by the ideal of prioritized aggregation operators bu R.R. Yager, we developed some prioritized aggregation operators for aggregating interval intuitionistic trapezoidal fuzzy information, and then apply them to develop some models for interval intuitionistic trapezoidal fuzzy multiple attribute decision making (MADM) problems in which the attributes are in different priority level. Finally, a practical example about talent introduction is given to verify the developed approaches and to demonstrate its practicality and effectiveness. Read More Read Less

Abstract Albeit the modeling and verification of the Multi-Agent Systems (MASs) have been since long under study, there are several related challenges that should still be addressed. In effect, several frameworks have been established for modeling and verifying the MASs with regard to communicative commitments. A bulky volume of research has been conducted for defining semantics of these systems. Though, formal verification of these... Albeit the modeling and verification of the Multi-Agent Systems (MASs) have been since long under study, there are several related challenges that should still be addressed. In effect, several frameworks have been established for modeling and verifying the MASs with regard to communicative commitments. A bulky volume of research has been conducted for defining semantics of these systems. Though, formal verification of these systems is still unresolved research problem. Within this context, this paper presents the CTLcom that reforms the CTLC, i.e., the temporal logic of the commitments, so as to enable reasoning about the communication and fulfillment of commitments. Moreover, the paper introduces a fully-automated method for verification of the logic by means of trimming down the problem of a model that checks the CTL com to a problem of a model that checks the GCTL”, which is a generalized version of the CTL” with action formulae. By so doing, we take advantage of the CWB-NC automata-based model checker as a tool for verification. Lastly, this paper presents a case study drawn from the business field, that is, the NetBill protocol, illustrates its implementation, and discusses the associated experimental results in order to illustrate the efficiency and effectiveness of the suggested technique. Read More Read Less