For a modem organization, KM （Knowledge Management） plays a critical role in terms of strategy development. Key determinants of KM lead to better understanding of various influences that enable and organisation to f...For a modem organization, KM （Knowledge Management） plays a critical role in terms of strategy development. Key determinants of KM lead to better understanding of various influences that enable and organisation to face competitors. For this reason, sharing and managing knowledge in an organization involves a series of activities that are related to the specific functional aspects of that organisation. In order to foster KM in an organisation, these functional aspects must be understood properly, and within the context of a given organisation, its geographical location and the cultural aspects of the given organisation. This was the premise on which this study was conducted with Indian organisations. A mixed method approach was used to understand the views of Indian region towards KM in this study, be selecting 400 participants in four major each cities. A second order regression model was built using Structural Equation Model to arrive at nine constructs that are relevant to KM in an organisation.展开更多
The development of the assistive abilities regarding the decision-making process o fan Intelligent Control System （ICS） like a fuzzy expert system implies the development of its functionality and its ability of spec...The development of the assistive abilities regarding the decision-making process o fan Intelligent Control System （ICS） like a fuzzy expert system implies the development of its functionality and its ability of specification. Fuzzy expert systems can model fuzzy controllers, i.e., the knowledge representation and the abilities of making decisions corresponding to fuzzy expert systems are much more complicated that in the case of standard fuzzy controllers. The expert system acts also as a supervisor, creating meta-level reasoning on a set of fuzzy controllers, in order to choose the best one for the management of the process. Knowledge Management Systems （KMSs） is a new development paradigm of Intelligent Systems which has resulted from a synergy between fuzzy sets, artificial neural networks, evolutionary computation, machine learning, etc., broadening computer science, physics, economics, engineering, mathematics. This paper presents, after a synergic new paradigm of intelligent systems, as a practical case study the fuzzy and temporal properties of knowledge formalism embedded in an ICS. We are not dealing high with level reasoning methods, because we think that real-time problems can only be solved by rather low-level reasoning. Solving the match-time predictability problem would allow us to build much more powerful reasoning techniques.展开更多
文摘For a modem organization, KM （Knowledge Management） plays a critical role in terms of strategy development. Key determinants of KM lead to better understanding of various influences that enable and organisation to face competitors. For this reason, sharing and managing knowledge in an organization involves a series of activities that are related to the specific functional aspects of that organisation. In order to foster KM in an organisation, these functional aspects must be understood properly, and within the context of a given organisation, its geographical location and the cultural aspects of the given organisation. This was the premise on which this study was conducted with Indian organisations. A mixed method approach was used to understand the views of Indian region towards KM in this study, be selecting 400 participants in four major each cities. A second order regression model was built using Structural Equation Model to arrive at nine constructs that are relevant to KM in an organisation.
文摘The development of the assistive abilities regarding the decision-making process o fan Intelligent Control System （ICS） like a fuzzy expert system implies the development of its functionality and its ability of specification. Fuzzy expert systems can model fuzzy controllers, i.e., the knowledge representation and the abilities of making decisions corresponding to fuzzy expert systems are much more complicated that in the case of standard fuzzy controllers. The expert system acts also as a supervisor, creating meta-level reasoning on a set of fuzzy controllers, in order to choose the best one for the management of the process. Knowledge Management Systems （KMSs） is a new development paradigm of Intelligent Systems which has resulted from a synergy between fuzzy sets, artificial neural networks, evolutionary computation, machine learning, etc., broadening computer science, physics, economics, engineering, mathematics. This paper presents, after a synergic new paradigm of intelligent systems, as a practical case study the fuzzy and temporal properties of knowledge formalism embedded in an ICS. We are not dealing high with level reasoning methods, because we think that real-time problems can only be solved by rather low-level reasoning. Solving the match-time predictability problem would allow us to build much more powerful reasoning techniques.
