Accurate and timely monthly rainfall forecasting is a major challenge for the scientific community in hydrological research such as river management project and design of flood warning systems. Support Vector Regressi...Accurate and timely monthly rainfall forecasting is a major challenge for the scientific community in hydrological research such as river management project and design of flood warning systems. Support Vector Regression (SVR) is a very useful precipitation prediction model. In this paper, a novel parallel co-evolution algorithm is presented to determine the appropriate parameters of the SVR in rainfall prediction based on parallel co-evolution by hybrid Genetic Algorithm and Particle Swarm Optimization algorithm, namely SVRGAPSO, for monthly rainfall prediction. The framework of the parallel co-evolutionary algorithm is to iterate two GA and PSO populations simultaneously, which is a mechanism for information exchange between GA and PSO populations to overcome premature local optimum. Our methodology adopts a hybrid PSO and GA for the optimal parameters of SVR by parallel co-evolving. The proposed technique is applied over rainfall forecasting to test its generalization capability as well as to make comparative evaluations with the several competing techniques, such as the other alternative methods, namely SVRPSO (SVR with PSO), SVRGA (SVR with GA), and SVR model. The empirical results indicate that the SVRGAPSO results have a superior generalization capability with the lowest prediction error values in rainfall forecasting. The SVRGAPSO can significantly improve the rainfall forecasting accuracy. Therefore, the SVRGAPSO model is a promising alternative for rainfall forecasting.展开更多
MATLAB software and optimal complete subgraph algorithm were used to extract and reveal the microsatellite distribution features in the complete genomes of the tobacco vein clearing virus （NC-003 378.1） from the NCB...MATLAB software and optimal complete subgraph algorithm were used to extract and reveal the microsatellite distribution features in the complete genomes of the tobacco vein clearing virus （NC-003 378.1） from the NCBI database.The results showed that the repetitions number and their location of the N-base group has been extracted and displayed.The largest repetitions of N-base group in the complete genomes of the tobacco vein clearing virus was decreased as the exponential function with the increasing of N.The method used in this study could be applied to the extraction and revealing of the microsatellite distribution features in the complete genomes of other viruses,thereby provided a basis for the research of the structure and the law of function,inheritance and variation by the using of the microsatellite distribution features.展开更多
It is important to harmonize effectively the behaviors of the agents in the multi-agent system (MAS) to complete the solution process. The co-evolution computing techniques, inspired by natural selection and genetics,...It is important to harmonize effectively the behaviors of the agents in the multi-agent system (MAS) to complete the solution process. The co-evolution computing techniques, inspired by natural selection and genetics, are usually used to solve these problems. Based on learning and evolution mechanisms of the biological systems, an adaptive co-evolution model was proposed in this paper. Inner-population, inter-population, and community learning operators were presented. The adaptive co-evolution algorithm (ACEA) was designed in detail. Some simulation experiments were done to evaluate the performance of the ACEA. The results show that the ACEA is more effective and feasible than the genetic algorithm to solve the optimization problems.展开更多
应用遗传算法相似性程序(GASP),以作用于I型人类免疫缺陷病毒(humanimmun-odeficiency virustype1,HIV-1)整合酶(IN)的二酮酸类(diketoacids,DKAs)抑制剂构建药效团模型.所选训练集分子均具有可靠的类药性特征及DKAs药效团特征.尝试将...应用遗传算法相似性程序(GASP),以作用于I型人类免疫缺陷病毒(humanimmun-odeficiency virustype1,HIV-1)整合酶(IN)的二酮酸类(diketoacids,DKAs)抑制剂构建药效团模型.所选训练集分子均具有可靠的类药性特征及DKAs药效团特征.尝试将抑制剂与药效团叠合后的构象和抑制剂与IN的对接构象进行叠合,得到药效团模型与分子对接构象中IN残基的相对位置,并基于抑制剂的药效团模型特征与周围IN氨基酸残基位置的匹配情况进行药效团特征的修改.所得最优药效团由1个疏水特征、3对氢键特征和1个氢键供体特征组成.该药效团的命中物质量(goodness of hit,GH)为0.56,产出率(Y)达63.6%,假阳性率(FP)为0.41%.该药效团具有较好的置信度,产出率较高而假阳性率较低,可用于数据库搜索发现新的具有DKAs药效团特征的活性化合物,也可为先导化合物的改造提供帮助.展开更多
文摘Accurate and timely monthly rainfall forecasting is a major challenge for the scientific community in hydrological research such as river management project and design of flood warning systems. Support Vector Regression (SVR) is a very useful precipitation prediction model. In this paper, a novel parallel co-evolution algorithm is presented to determine the appropriate parameters of the SVR in rainfall prediction based on parallel co-evolution by hybrid Genetic Algorithm and Particle Swarm Optimization algorithm, namely SVRGAPSO, for monthly rainfall prediction. The framework of the parallel co-evolutionary algorithm is to iterate two GA and PSO populations simultaneously, which is a mechanism for information exchange between GA and PSO populations to overcome premature local optimum. Our methodology adopts a hybrid PSO and GA for the optimal parameters of SVR by parallel co-evolving. The proposed technique is applied over rainfall forecasting to test its generalization capability as well as to make comparative evaluations with the several competing techniques, such as the other alternative methods, namely SVRPSO (SVR with PSO), SVRGA (SVR with GA), and SVR model. The empirical results indicate that the SVRGAPSO results have a superior generalization capability with the lowest prediction error values in rainfall forecasting. The SVRGAPSO can significantly improve the rainfall forecasting accuracy. Therefore, the SVRGAPSO model is a promising alternative for rainfall forecasting.
基金Supported by the Eleventh Five-year Development Planning Project for Instructional Science in Hubei Province (2006B131)~~
文摘MATLAB software and optimal complete subgraph algorithm were used to extract and reveal the microsatellite distribution features in the complete genomes of the tobacco vein clearing virus （NC-003 378.1） from the NCBI database.The results showed that the repetitions number and their location of the N-base group has been extracted and displayed.The largest repetitions of N-base group in the complete genomes of the tobacco vein clearing virus was decreased as the exponential function with the increasing of N.The method used in this study could be applied to the extraction and revealing of the microsatellite distribution features in the complete genomes of other viruses,thereby provided a basis for the research of the structure and the law of function,inheritance and variation by the using of the microsatellite distribution features.
基金Project of Shanghai Committee of Science and Technology, China ( No.08JC1400100, No. QB081404100)Leading Academic Discipline Project of Shanghai Municipal Education Commission, China (No.J51901)
文摘It is important to harmonize effectively the behaviors of the agents in the multi-agent system (MAS) to complete the solution process. The co-evolution computing techniques, inspired by natural selection and genetics, are usually used to solve these problems. Based on learning and evolution mechanisms of the biological systems, an adaptive co-evolution model was proposed in this paper. Inner-population, inter-population, and community learning operators were presented. The adaptive co-evolution algorithm (ACEA) was designed in detail. Some simulation experiments were done to evaluate the performance of the ACEA. The results show that the ACEA is more effective and feasible than the genetic algorithm to solve the optimization problems.
文摘应用遗传算法相似性程序(GASP),以作用于I型人类免疫缺陷病毒(humanimmun-odeficiency virustype1,HIV-1)整合酶(IN)的二酮酸类(diketoacids,DKAs)抑制剂构建药效团模型.所选训练集分子均具有可靠的类药性特征及DKAs药效团特征.尝试将抑制剂与药效团叠合后的构象和抑制剂与IN的对接构象进行叠合,得到药效团模型与分子对接构象中IN残基的相对位置,并基于抑制剂的药效团模型特征与周围IN氨基酸残基位置的匹配情况进行药效团特征的修改.所得最优药效团由1个疏水特征、3对氢键特征和1个氢键供体特征组成.该药效团的命中物质量(goodness of hit,GH)为0.56,产出率(Y)达63.6%,假阳性率(FP)为0.41%.该药效团具有较好的置信度,产出率较高而假阳性率较低,可用于数据库搜索发现新的具有DKAs药效团特征的活性化合物,也可为先导化合物的改造提供帮助.
