The fault diagnosis model for FMS based on multi layer feedforward neural networks was discussed An improved BP algorithm,the tactic of initial value selection based on genetic algorithm and the method of network st...The fault diagnosis model for FMS based on multi layer feedforward neural networks was discussed An improved BP algorithm,the tactic of initial value selection based on genetic algorithm and the method of network structure optimization were presented for training this model ANN(artificial neural network)fault diagnosis model for the robot in FMS was made by the new algorithm The result is superior to the rtaditional algorithm展开更多
In recent years,researchers have been attempting to relate differences in personality(e.g.,boldness,aggressiveness,exploration tendency)to variation in cognition(performances in tasks that require learning,reasoning,a...In recent years,researchers have been attempting to relate differences in personality(e.g.,boldness,aggressiveness,exploration tendency)to variation in cognition(performances in tasks that require learning,reasoning,attention,or memory,etc.)both theoretically and empirically.However,it is unclear on what basis personality and cognition might be associated with each other.Previous theory suggests a connection between fast–slow personality types and cognitive speed–accuracy tradeoffs.In this study,we tested this hypothesis in budgerigars and found that,in their 1st associative learning,birds with fast personality(less fearful of handling stress)were fast learners in the beginning,while slow personality individuals improved faster,but both types of birds did not differ in accuracy.However,these relationships were context-dependent.No significant relationship was found in subsequent learning tasks(reversal learning and a 2nd associative learning)in the familiar context(task setup and apparatus similar to the 1st associative learning).We then conducted a problem-solving experiment with novel setup and apparatus to test 1 possible explanation that the association between personality and cognition in the 1st associative learning might be caused by noncognitive constraint,such as fearfulness when facing novel task setup and apparatus.We found that fast individuals interacted more with the problem box and solved it,whereas the slow birds were not.We suggest that personalities can influence cognitive performances and trigger a cognitive speed-improvement tradeoff under the novel context.However,there are no consistent cognitive styles that co-varied with different personalities.展开更多
文摘The fault diagnosis model for FMS based on multi layer feedforward neural networks was discussed An improved BP algorithm,the tactic of initial value selection based on genetic algorithm and the method of network structure optimization were presented for training this model ANN(artificial neural network)fault diagnosis model for the robot in FMS was made by the new algorithm The result is superior to the rtaditional algorithm
基金This study was supported by the National Natural Science Foundation of China(Project No.31501868 and No.32070445)Fundamental Research Funds for the Central Universities(Project No.lzujbky-2020-ct02).
文摘In recent years,researchers have been attempting to relate differences in personality(e.g.,boldness,aggressiveness,exploration tendency)to variation in cognition(performances in tasks that require learning,reasoning,attention,or memory,etc.)both theoretically and empirically.However,it is unclear on what basis personality and cognition might be associated with each other.Previous theory suggests a connection between fast–slow personality types and cognitive speed–accuracy tradeoffs.In this study,we tested this hypothesis in budgerigars and found that,in their 1st associative learning,birds with fast personality(less fearful of handling stress)were fast learners in the beginning,while slow personality individuals improved faster,but both types of birds did not differ in accuracy.However,these relationships were context-dependent.No significant relationship was found in subsequent learning tasks(reversal learning and a 2nd associative learning)in the familiar context(task setup and apparatus similar to the 1st associative learning).We then conducted a problem-solving experiment with novel setup and apparatus to test 1 possible explanation that the association between personality and cognition in the 1st associative learning might be caused by noncognitive constraint,such as fearfulness when facing novel task setup and apparatus.We found that fast individuals interacted more with the problem box and solved it,whereas the slow birds were not.We suggest that personalities can influence cognitive performances and trigger a cognitive speed-improvement tradeoff under the novel context.However,there are no consistent cognitive styles that co-varied with different personalities.
