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The feature subset selection, along with the parameters of classifier significantly influences the classification accuracy. In order to ensure the optimal classification performance, the artificial bee colony (ABC) algorithm is proposed to simultaneously optimize the feature subset and the parameters of support vector machines (SVM), meanwhile for improving the optimizing performance of ABC algorithm,...
A novel multi-relay selection algorithm based on genetic algorithm (GA) in dual-hop decode- and-forward cooperative network is presented. The quality of service is expressed by the condition that the SNR of destination should be larger than 22R -- 1 according to Shannon information capacity, in which R is its data-rate requirement. Moreover, residual energy status parameter of the network using the...
In the study of identifying homogeneous regions in remote sensing images, fuzzy clustering is one of the most frequently used algorithms. Commonly used method of fuzzy cluster analysis is the fuzzy C-means algorithm(FCM), which easily traps into local optimal solution. An algorithm combining FCM with genetic algorithms is introduced for aerial remote sensing image fuzzy clustering analysis. The input...
FastICA and Infomax are the most popular algorithms for calculating independent components. These two optimization process usually lead to unstable results. To overcome this drawback, a genetic algorithm for independent component analysis has been developed with enhancement of the independence of the resulting components. By modifying the FastICA to start from given initial point and adopting a new...
This paper presents an original usage of genetic algorithm in application to 2-D aerial image registration with position and similarity constraints. The framework of the presented method includes four steps: feature points extraction, mesh generation, mesh registration and image registration. First, the position and inner position constraints are selected based on the visual features manually or automatically...
Considering that the high concentration of mine gas and hydrogen will disturb the output of electrochemical carbon monoxide sensor, this paper integrates gas sensor array with data fusion Algorithm. The output signals of three sensors are trained by BP neural network to get the mathematical model of information fusion for the analysis of mixed gas of methane, hydrogen and carbon monoxide. The experiment...
This paper proposes a new method for mid-long term load forecasting-fuzzy rules by genetic algorithms based on Takagi-Sugeno Fuzzy Logic System, and establishing the fuzzy model for load forecasting. lt can be seen from the example this method can improve effectively the forecast accuracy and speed. It can be applied to the mid-long term electric load forecasting.
This paper proposes a new method for load forecasting-fuzzy rules by genetic algorithms based on Takagi-Sugeno fuzzy logic system, and establishing the fuzzy model for load forecasting. It can be seen from the example this method can improve effectively the forecast accuracy and speed. It can be applied to the daily electric load forecasting.
This paper proposes a new method for load forecasting-fuzzy rules by genetic algorithms based on Takagi-Sugeno Fuzzy Logic System, and establishing the fuzzy model for load forecasting. It can be seen from the example this method can improve effectively the forecast accuracy and speed. It can be applied to the short-term electric load forecasting.
In the study, neural network theory was used to build a nonlinear model for high precision gyroscope reflecting the relationship between temperature and drift.The result shows that types of neural network and input sample have great influence on model precision. High precision gyroscope is sensitive to temperature. The input sample must take account of the continuous temperature and mean temperature...
In the study, back-propagation neural networks (BP-NN) theory and genetic algorithm (GA) were used to build a nonlinear prediction model reflecting the relationship between technics parameters of electric field aging and mechanical properties of LY12 aluminum alloy. In this model, electric field intensity, aging temperature and time were as input parameters. Tensile strength, yield strength and micro-yield...
Ant Colony Optimization (ACO) , an intelligent swarm algorithm, proves effective in various fields. However, the choice of the first route and the initial distribution of pheromone are among the toughest yet most crucial factors in determining the performance of process optimization. According to the materials we referred to, almost all the existing methods of ACO set the same constant in all routes...
Support vector machine (SVM) plays an important role in the data mining and knowledge discovery by constructing a non-linear optimal classifier. The key problem of training support vector machines is how to solve quadratic programming problem, which results in calculation difficulty while learning samples gets larger. The intelligent search techniques, such as genetic algorithm and particle swarm...
Due to the uncertainty of future demand, companies have changed their production planning mode from pre-planning to produce according to the accepted orders, which is named as make-to-order (MTO) or build-to-order (BTO). The hypothesis of independent demand, which falls short of the real state, has been widely introduced in the model of traditional production planning. In general, the future demand...
This paper proposes to leverage multi-source multi-path diversity to design a video streaming system for supporting concurrent video-on-demand (VoD) services over wireless mesh networks (WMNs). By integrating a wireless interference model into consideration, we have a more realistic network model to capture the characteristics of wireless networks. Based on that, we mathematically formulate the route...
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