By combining the advantages of the additive weighted mean (AWM) operator and the ordered weighted averaging (OWA) operator, this paper first presents a hybrid operator for aggregating data information, and then propos...By combining the advantages of the additive weighted mean (AWM) operator and the ordered weighted averaging (OWA) operator, this paper first presents a hybrid operator for aggregating data information, and then proposes a hybrid aggregation (HA) operator-based method for multiple attribute decision making (MADM) problems. The theoretical analyses and the numerical results show that the HA operator generalizes both the AWM and OWA operators, and reflects the importance of both the given argument and the ordered position of the argument. Thus, the HA operator can reflect better real situations in practical applications. Finally, an illustrative example is given.展开更多
In game theoretic context, it is assumed that the decision maker has the extraordinary skills of reasoning and calculation. This assumption is called ＂perfect rationality＂. A player with perfect rationality can solv...In game theoretic context, it is assumed that the decision maker has the extraordinary skills of reasoning and calculation. This assumption is called ＂perfect rationality＂. A player with perfect rationality can solve complex problems without making mistakes. However, recently, many studies have restricted this rationality or the structure of game. These restrictions are called ＂bounded rationality.＂ The authors also focus on bounded rationality, but with learning dynamics and complex networks. A complex network covers a wide area. Currently, a wide range of studies have not only investigated network formation and the characteristics of a formed network, but also analyzed situations where a network is already provided. In addition, in an analysis using game theory, a prisoners＇ dilemma type game was used to investigate how a change in the network structure would affect the players＇ relationships Therefore, our model employs decision makers with learning dynamics and describes the interaction of decision makers as a network. The purpose of this study is to examine the behavior of the decision maker with learning dynamics and the formation of networks by the interaction of decision makers through an agent-based simulation.展开更多
Applications can only reach 8 %~15 % of utilization on modern computer systems. There are many obstacles to improving system efficiency. The key root is the conflict between the fixed general computer architecture and...Applications can only reach 8 %~15 % of utilization on modern computer systems. There are many obstacles to improving system efficiency. The key root is the conflict between the fixed general computer architecture and the variable requirements of applications. Proactive reconfigurable computing architecture(PRCA) is proposed to improve computing efficiency. PRCA dynamically constructs an efficient computing architecture for a specific application via reconfigurable technology by perceiving requirements,workload and utilization of computing resources. Proactive decision support system(PDSS),hybrid reconfigurable computing array(HRCA) and reconfigurable interconnect(RIC) are intensively researched as the key technologies. The principles of PRCA have been verified with four applications on a test bed. It is shown that PRCA is feasible and highly efficient.展开更多
Product analytics is a blend of computational methods with the express purpose of facilitating the multifaceted process of decision-making based on demographic and consumer preferences. This complex subject is derived...Product analytics is a blend of computational methods with the express purpose of facilitating the multifaceted process of decision-making based on demographic and consumer preferences. This complex subject is derived from consensus theory and includes structured analytics, categories, and the combination of evidence. The methodology is applicable to a wide range of business, economic, social, political, and strategic decisions. The paper describes a product allocation application to demonstrate the conceots.展开更多
文摘By combining the advantages of the additive weighted mean (AWM) operator and the ordered weighted averaging (OWA) operator, this paper first presents a hybrid operator for aggregating data information, and then proposes a hybrid aggregation (HA) operator-based method for multiple attribute decision making (MADM) problems. The theoretical analyses and the numerical results show that the HA operator generalizes both the AWM and OWA operators, and reflects the importance of both the given argument and the ordered position of the argument. Thus, the HA operator can reflect better real situations in practical applications. Finally, an illustrative example is given.
文摘In game theoretic context, it is assumed that the decision maker has the extraordinary skills of reasoning and calculation. This assumption is called ＂perfect rationality＂. A player with perfect rationality can solve complex problems without making mistakes. However, recently, many studies have restricted this rationality or the structure of game. These restrictions are called ＂bounded rationality.＂ The authors also focus on bounded rationality, but with learning dynamics and complex networks. A complex network covers a wide area. Currently, a wide range of studies have not only investigated network formation and the characteristics of a formed network, but also analyzed situations where a network is already provided. In addition, in an analysis using game theory, a prisoners＇ dilemma type game was used to investigate how a change in the network structure would affect the players＇ relationships Therefore, our model employs decision makers with learning dynamics and describes the interaction of decision makers as a network. The purpose of this study is to examine the behavior of the decision maker with learning dynamics and the formation of networks by the interaction of decision makers through an agent-based simulation.
文摘Applications can only reach 8 %~15 % of utilization on modern computer systems. There are many obstacles to improving system efficiency. The key root is the conflict between the fixed general computer architecture and the variable requirements of applications. Proactive reconfigurable computing architecture(PRCA) is proposed to improve computing efficiency. PRCA dynamically constructs an efficient computing architecture for a specific application via reconfigurable technology by perceiving requirements,workload and utilization of computing resources. Proactive decision support system(PDSS),hybrid reconfigurable computing array(HRCA) and reconfigurable interconnect(RIC) are intensively researched as the key technologies. The principles of PRCA have been verified with four applications on a test bed. It is shown that PRCA is feasible and highly efficient.
文摘Product analytics is a blend of computational methods with the express purpose of facilitating the multifaceted process of decision-making based on demographic and consumer preferences. This complex subject is derived from consensus theory and includes structured analytics, categories, and the combination of evidence. The methodology is applicable to a wide range of business, economic, social, political, and strategic decisions. The paper describes a product allocation application to demonstrate the conceots.
