Complex behavior in a selective aging simple neuron model based on small world networks is investigated. The basic elements of the model are endowed with the main features of a neuron function. The structure of the se...Complex behavior in a selective aging simple neuron model based on small world networks is investigated. The basic elements of the model are endowed with the main features of a neuron function. The structure of the selective aging neuron model is discussed. We also give some properties of the new network and find that the neuron model displays a power-law behavior. If the brain network is small world-like network, the mean avalanche size is almost the same unless the aging parameter is big enough.展开更多
In this paper, a new technique using artificial neural networks for power system state estimation is presented. This method does not require network observability analysis and uses fewer measurement variables than con...In this paper, a new technique using artificial neural networks for power system state estimation is presented. This method does not require network observability analysis and uses fewer measurement variables than conventional techniques. This approach has been successfully implemented on six-bus, 18-bus, IEEE 14-bus and IEEE 57-bus power systems and the results show that this method is very accurate and a lot faster than conventional techniques making it ideal for smart grid applications.展开更多
OBJECTIVE: To apply data mining methods to research on the state of sub-mental health among residents in eight provinces and cities in China and to mine latent knowledge about many conditions through data mining and a...OBJECTIVE: To apply data mining methods to research on the state of sub-mental health among residents in eight provinces and cities in China and to mine latent knowledge about many conditions through data mining and analysis of data on 3970 sub-mentally healthy individuals selected from 13385 relevant question naires.METHODS: The strategic tree algorithm was used to identify the main mani festations of the state of sub-mental health. The backpropogation artificial neural network was used to analyze the main mani festations of sub-healthy mental states of three different degrees. A sub-mental health evaluation model was then established to achieve predictive evaluationresults.RESULTS: Using classifications from the Scale of Chinese Sub-healthy State, the main manifestations of sub-mental health selected using the strate gictree were F1101(Do you lack peace of mind?),F1102(Are you easily nervous when something comes up?), and F1002(Do you often sigh?). The relative intensity of manifestations of sub-mental health was highest for F1101, followed by F1102,and then F1002. Through study of the neural network, better differentiation could be made between moderate and severe and between mild and severe states of sub-mental health. The differentiation between mild and moderate sub-mental health states was less apparent. Additionally, the sub-mental health state evaluation model, which could be used to predict states of sub-mental health of different individuals, was established using F1101, F1102, F1002, and the mental self-assessment totals core.CONCLUSION: The main manifestations of the state of sub-mental health can be discovered using data mining methods to research and analyze the latent laws and knowledge hidden in research evidence on the state of sub-mental health. The state of sub-mental health of different individuals can be rapidly predicted using the model established here.This can provide a basis for assessment and intervention for sub-mental health. It can also replace the relatively outdated approaches to research on sub-health in the technical era of information and digitization by combining the study of states of sub-mental health with information techniques and by further quantifying the relevant information.展开更多
基金National Natural Science Foundation of China under Grant No.10675060
文摘Complex behavior in a selective aging simple neuron model based on small world networks is investigated. The basic elements of the model are endowed with the main features of a neuron function. The structure of the selective aging neuron model is discussed. We also give some properties of the new network and find that the neuron model displays a power-law behavior. If the brain network is small world-like network, the mean avalanche size is almost the same unless the aging parameter is big enough.
文摘In this paper, a new technique using artificial neural networks for power system state estimation is presented. This method does not require network observability analysis and uses fewer measurement variables than conventional techniques. This approach has been successfully implemented on six-bus, 18-bus, IEEE 14-bus and IEEE 57-bus power systems and the results show that this method is very accurate and a lot faster than conventional techniques making it ideal for smart grid applications.
基金Supported by Chinese"Disease"Sub-health Medicine Research and Intervention of the Eleventh Five-Year Science and Technology Support Project of China(No.2006BAI13B01)Financial Support Case Studies of Traditional Chinese Medicine Treatment of Disease and Health Management Ideas of Shanghai Health Bureau(No.2010227)+2 种基金Scientific Innovation Research Funds of Shanghai Municipal Education Commission(No.14YZ061)Teacher Academic Community Fund of Shanghai University of Traditional Chinese Medicine(No.2013JXG03)Chinese Culture and Its Core Value System Modernization Transformation of the National Social Science Funds(No.12AZD094)
文摘OBJECTIVE: To apply data mining methods to research on the state of sub-mental health among residents in eight provinces and cities in China and to mine latent knowledge about many conditions through data mining and analysis of data on 3970 sub-mentally healthy individuals selected from 13385 relevant question naires.METHODS: The strategic tree algorithm was used to identify the main mani festations of the state of sub-mental health. The backpropogation artificial neural network was used to analyze the main mani festations of sub-healthy mental states of three different degrees. A sub-mental health evaluation model was then established to achieve predictive evaluationresults.RESULTS: Using classifications from the Scale of Chinese Sub-healthy State, the main manifestations of sub-mental health selected using the strate gictree were F1101(Do you lack peace of mind?),F1102(Are you easily nervous when something comes up?), and F1002(Do you often sigh?). The relative intensity of manifestations of sub-mental health was highest for F1101, followed by F1102,and then F1002. Through study of the neural network, better differentiation could be made between moderate and severe and between mild and severe states of sub-mental health. The differentiation between mild and moderate sub-mental health states was less apparent. Additionally, the sub-mental health state evaluation model, which could be used to predict states of sub-mental health of different individuals, was established using F1101, F1102, F1002, and the mental self-assessment totals core.CONCLUSION: The main manifestations of the state of sub-mental health can be discovered using data mining methods to research and analyze the latent laws and knowledge hidden in research evidence on the state of sub-mental health. The state of sub-mental health of different individuals can be rapidly predicted using the model established here.This can provide a basis for assessment and intervention for sub-mental health. It can also replace the relatively outdated approaches to research on sub-health in the technical era of information and digitization by combining the study of states of sub-mental health with information techniques and by further quantifying the relevant information.
