In this paper,the generation of maximally generalized rules in the course of classitication knowledge discovery based on rough sets theory is discussed. Firstly, an algorithm is introduced. Secondly,we propose that th...In this paper,the generation of maximally generalized rules in the course of classitication knowledge discovery based on rough sets theory is discussed. Firstly, an algorithm is introduced. Secondly,we propose that the information-based J-measure is used as another measure of attribute signifi cance value. This measure is used for heuristically selecting the conditions to be removed in the process of extracting a set of maximally generalized rules. Finally,we present an example to illustrate the process of the algorithm.展开更多
This paper proposes a new neural fuzzy inference system that mainly consists of four parts. The first part is about how to use neural network to express the relation within a fuzzy rule. The second part is the simplif...This paper proposes a new neural fuzzy inference system that mainly consists of four parts. The first part is about how to use neural network to express the relation within a fuzzy rule. The second part is the simplification of the first part, and experiments show that these simplifications work. On the contrary to the second part, the third part is the enhancement of the first part and it can be used when the first part cannot work very well in the fuzzy inference algorithm, which would be introduced in the fourth part. Finally, the fourth part "neural fuzzy inference algorithm" is been introduced. It can inference the new membership function of the output based on previous fuzzy rules. The accuracy of the fuzzy inference algorithm is dependent on neural network generalization ability. Even if the generalization ability of the neural network we used is good, we still get inaccurate results since the new coming rule may not be related to any of the previous rules. Experiments show this algorithm is successful in situations which satisfy these conditions.展开更多
The potential energy landscape of the neutral Ni_(2)(CO)_(5) complex was re-examined.A new C_(2v) structure with double bridging carbonyls is found to compete with the previously proposed triply carbonyl-bridged D_(3h...The potential energy landscape of the neutral Ni_(2)(CO)_(5) complex was re-examined.A new C_(2v) structure with double bridging carbonyls is found to compete with the previously proposed triply carbonyl-bridged D_(3h) isomer for the global minimum of Ni_(2)(CO)_(5).Despite that the tri-bridged isomer possesses the more favored(18,18)configuration,where both metal centers satisfy the 18-electron rule,the neutral Ni_(2)(CO)_(5) complex prefers the di-bridged geometry with(18,16)configuration.The isomerization energy decomposition analysis reveals that the structural preference is a consequence of the maximization of electrostatic and orbital interactions.展开更多
文摘In this paper,the generation of maximally generalized rules in the course of classitication knowledge discovery based on rough sets theory is discussed. Firstly, an algorithm is introduced. Secondly,we propose that the information-based J-measure is used as another measure of attribute signifi cance value. This measure is used for heuristically selecting the conditions to be removed in the process of extracting a set of maximally generalized rules. Finally,we present an example to illustrate the process of the algorithm.
文摘This paper proposes a new neural fuzzy inference system that mainly consists of four parts. The first part is about how to use neural network to express the relation within a fuzzy rule. The second part is the simplification of the first part, and experiments show that these simplifications work. On the contrary to the second part, the third part is the enhancement of the first part and it can be used when the first part cannot work very well in the fuzzy inference algorithm, which would be introduced in the fourth part. Finally, the fourth part "neural fuzzy inference algorithm" is been introduced. It can inference the new membership function of the output based on previous fuzzy rules. The accuracy of the fuzzy inference algorithm is dependent on neural network generalization ability. Even if the generalization ability of the neural network we used is good, we still get inaccurate results since the new coming rule may not be related to any of the previous rules. Experiments show this algorithm is successful in situations which satisfy these conditions.
基金supported by the National Natural Science Foundation of China(No.21571119 and No.21603130)the Shanxi Province Science Foundation for Youths(No.201901D211395)+1 种基金the 1331 Engineering of Shanxi Provincethe Start-up fund from Shanxi Normal University。
文摘The potential energy landscape of the neutral Ni_(2)(CO)_(5) complex was re-examined.A new C_(2v) structure with double bridging carbonyls is found to compete with the previously proposed triply carbonyl-bridged D_(3h) isomer for the global minimum of Ni_(2)(CO)_(5).Despite that the tri-bridged isomer possesses the more favored(18,18)configuration,where both metal centers satisfy the 18-electron rule,the neutral Ni_(2)(CO)_(5) complex prefers the di-bridged geometry with(18,16)configuration.The isomerization energy decomposition analysis reveals that the structural preference is a consequence of the maximization of electrostatic and orbital interactions.
