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Interconnected power systems experienced a significant increase in size and complexity. It is computationally burdensome to represent the entire system in detail to conduct power system analysis. Therefore, the model of the study system must be retained in detail while the external system can be reduced using system reduction techniques. This paper proposes a measurement-based dynamic equivalent in...
Existing clustering algorithms need to specify the number of clusters and to select initial points using human input, which lead to inferior clustering and optimisation outputs. Here, an improved grey decision-making model based on the thought of affinity propagation algorithm and grey correlation analysis is proposed to solve these problems. According to the panel data class and the inter-class candidate...
To retrain an existing multilayer perceptron (MLP) on-line using newly observed data, it is necessary to incorporate the new information while preserving the performance of the network. This is known as the “plasticitystability” problem. For this purpose, we proposed an algorithm for on-line training with guide data (OLTA-GD). OLTA-GD is good for implementation in portable/wearable computing devices...
It is certain that the individual learners should be different from each other in order for a committee machine to reach the better performance. However, differences alone among the individual learners are not enough for the committee machine to predict well on the unknown data. It would be essential for each individual learner to be able to decide whether to learn to be different or not to the other...
In this paper, we propose a method for generating guide data, and investigate its efficiency and efficacy for on-line learning with guide data. On-line learning in this research updates a learning model initialized by the decision boundary making algorithm proposed by us in our earlier study. The problem is that, if the guide data are not properly generated, on-line learning may require high computational...
We compare the performance of multilayer perceptrons (MLPs) obtained using back propagation (BP), decision boundary making (DBM) algorithm and extreme learning machine (ELM), and investigate better method for developing aware agents (A-agent) that are suitable for implementation in portable/wearable computing devices (P/WCD). The DBM has been proposed by us for inducing compact and high performance...
Negative correlation learning has been proposed to create a set of negatively correlated artificial neural networks (ANNs) in a committee machine. In negative correlation learning, the error signals for each ANN on a given data are not only decided by the error differences between the output of ANN and the targets. Two terms are optimized at the same time. The first one is to minimize the error between...
Different to other re-sampling ensemble learning, negative correlation learning trains all individual models in an ensemble simultaneously and cooperatively. In negative correlation learning, each individual could see all training data, and adapt its target function based on what the rest of individuals in the ensemble have learned. In this paper, two error bounds are introduced in negative correlation...
Aiming at the atrocious storage environment of missile solid rocket motor, especially the higher requirement for structural reliability, based on the modified Arrhenius and GM-BP methods, the solid rocket motor life prediction principle was proposed. Using these methods, the engine life estimate and the propulsion system store life prediction model were founded. The modified Arrhenius method suits...
To deal with multi-modality in human pose estimation, mixture models or local models are introduced. However, problems with over-fitting and generalization are caused by our necessarily limited data, and the regression parameters need to be determined without resorting to slow and processor-hungry techniques, such as cross validation. To compensate these problems, we have developed a semi-parametric...
Software development often involves lots of domains, the models in different domains require different modeling elements. By metamodeling, we can formulate an appropriate meta-model and define domain modeling language according to domains that require. Combine domain modeling and MDA(Model Driven Architecture), metamodeling can greatly enchance the efficiency of software development. Firstly, this...
A non-grid-connected wind power system is a complex system that includes several subsystems such as a wind turbine subsystem, non-grid-connected electric generator subsystems, a non-grid-connected wind power control subsystem, gas-solid coupling vibration subsystems, and high-energy-consuming special load subsystems. It is a multi-objective, multi-factor, higher-order non-linear dynamics of large-scale...
The rainfall intensity-duration-frequency (idf) relationship is one of the most commonly used tools in water resources engineering. The idf relationships for traditional method are based on an at-site frequency analysis of rainfall data separately for different durations. So the researchers are focus on the distribution selection for each duration and the empirical formula to evaluate the rainfall...
Marine cage fish farming has grown dramatically during the last three decades in coastal counties worldwide, however, its adverse environmental impact has already led to growing concerns. The control of carrying capacity is a key problem for cage fish farming. Based on the fish stock and eco-environment survey data in a cage fish farm area and its vicinity in Dapeng Ao Cove, Daya Bay, South China...
Sensor web applications such as real-time environmental decision support systems require the use of sensors from multiple heterogeneous sources for purposes beyond the scope of the original sensor design and deployment. In such cyberenvironments, provenance plays a critical role as it enables users to understand, verify, reproduce, and ascertain the quality of derived data products. Such capabilities...
Computational intelligence, including mathematical modeling and statistical analysis, is always used in economy activities for quantitative analysis. For agriculture is so important that almost all states and regions pay special attention to its development. This paper collects China's 25 provinces agricultural fiscal support data and agriculture production cost data, analyzes the data with panel-data...
In order to break the bulwark and eliminate the information isolated island in UGIS, the architecture of SOA-oriented urban spatial information platform is proposed. The SOA-oriented urban spatial information management and service architecture is designed and the key technologies are discussed in detail. The architecture is based on service and adopts the convenient and widely used SOA. It contains...
In this thesis, memory principle and ant colony algorithm are fused and applied in intrusion detection system. The method of controlling pheromone used in ant colony algorithm is applied to simulate the memory process of human brain, and the concept of pheromone is put forth. The processes of memorizing and forgetting are reasonably interpreted through the increase and decrease of pheromone, and in...
Sequence alignment algorithms, which are hardly to be efficient, are frequently used in protein sequences analysis. In order to improve the analyzing efficiency, an improved PST(Probabilistic Suffix Trees) model is proposed in this paper. Firstly, by analyzing the similarity between protein sequences analysis and sequences data mining, the idea of using PST model to analyze protein sequences is presented;...
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