With its wide use in different fields, the problem of the convergence of simple genetic algorithms (GAs) has been concerned. In the past, the research on the convergence of GAs was based on Holland's model theorem...With its wide use in different fields, the problem of the convergence of simple genetic algorithms (GAs) has been concerned. In the past, the research on the convergence of GAs was based on Holland's model theorem. The diversity of the evolutionary population and the convergence of GAs are studied by using the concept of negentropy based on the discussion of the characteristic of GA. Some test functions are used to test the convergence of GAs, and good results have been obtained. It is shown that the global optimization may be obtained by selecting appropriate parameters of simple GAs if the evolution time is enough.展开更多
Enlightened by distribution of creatures in natural ecology environment, the distributionpopulation-based genetic algorithm (DPGA) is presented in this paper. The searching capability ofthe algorithm is improved by co...Enlightened by distribution of creatures in natural ecology environment, the distributionpopulation-based genetic algorithm (DPGA) is presented in this paper. The searching capability ofthe algorithm is improved by competition between distribution populations to reduce the search zone.This method is applied to design of optimal parameters of PID controllers with examples, and thesimulation results show that satisfactory performances are obtained.展开更多
Weedy rice exerts a severe impact on rice production by competing for sunlight, water and nutrients. This study assayed the population structure, genetic diversity and origin of Northeast Asia weedy rice by using 48 s...Weedy rice exerts a severe impact on rice production by competing for sunlight, water and nutrients. This study assayed the population structure, genetic diversity and origin of Northeast Asia weedy rice by using 48 simple sequence repeat markers. The results showed that weedy rice in Northeast Asia had a high genetic diversity, with Shannon＇s diversity index （I） of 0.748 and the heterozygosity （He） of 0.434. In each regional population, I value varied widely. The widest range of I （0.228-0.489） was observed in the weedy rice of Eastern China, which was larger than that of Northeast China and Korea （0.168-0.270）. The F-statistics of regional populations （Fis, Fit and Fst） also showed higher values in the weedy rice of Eastern China than those of Northeast China and Korea All weedy rice accessions were grouped into two clusters in the unweighted pair group method with arithmetic mean cluster analysis dendrogram, namely Eastern China branch and Northeastern China plus Korea branch. There was significant differentiation in genetic characteristics in weedy rice of northeastern and eastern Asia, especially in Eastern China.展开更多
The direct torque control of the dual star induction motor(DTC-DSIM) using conventional PI controllers is characterized by unsatisfactory performance, such as high ripples of torque and flux, and sensitivity to parame...The direct torque control of the dual star induction motor(DTC-DSIM) using conventional PI controllers is characterized by unsatisfactory performance, such as high ripples of torque and flux, and sensitivity to parametric variations. Among the most evoked control strategies adopted in this field to overcome these drawbacks presented in classical drive, it is worth mentioning the use of the second order sliding mode control(SOSMC) based on the super twisting algorithm(STA) combined with the fuzzy logic control(FSOSMC). In order to realize the optimal control performance, the FSOSMC parameters are adjusted using an optimization algorithm based on the genetic algorithm(GA). The performances of the envisaged control scheme, called G-FSOSMC, are investigated against G-SOSMC, G-PI and BBO-FSOSMC algorithms. The proposed controller scheme is efficient in reducing the torque and flux ripples, and successfully suppresses chattering. The effects of parametric uncertainties do not affect system performance.展开更多
To investigate the genetic variation and population structure of Pacific herring in the Yellow Sea and the genetic differentiation between the Yellow Sea and the Sea of Japan, fragments of 479-bp mitochondrial DNA con...To investigate the genetic variation and population structure of Pacific herring in the Yellow Sea and the genetic differentiation between the Yellow Sea and the Sea of Japan, fragments of 479-bp mitochondrial DNA control region were sequenced for 110 individuals collected from three different periods in the Yellow Sea and one locality in the Sea of Japan. High haplotype diversity and moderate nucleotide diversity were observed in Pacific herring. AMOVA and exact test of population differentiation showed no significant genetic differentiations among the three populations of the Yellow Sea and suggested the populations can be treated as a single panmictic stock in the Yellow Sea. However, a large and significant genetic differentiation （ФST=0.11; P=0.00） was detected between the populations in the Yellow Sea and the Sea of Japan. The high sea water temperature in the Tsushima Strait was thought a barrier to block the gene exchange between populations of the two sea areas. The neutrality tests and mismatch distribution indicated recent population expansion in Pacific herring.展开更多
An improved genetic algorithm (GA) is proposed based on the analysis of population diversity within the framework of Markov chain. The chaos operator to combat premature convergence concerning two goals of maintaining...An improved genetic algorithm (GA) is proposed based on the analysis of population diversity within the framework of Markov chain. The chaos operator to combat premature convergence concerning two goals of maintaining diversity in the population and sustaining the convergence capacity of the GA is introduced. In the CHaos Genetic Algorithm (CHGA), the population is recycled dynamically whereas the most highly fit chromosome is intact so as to restore diversity and reserve the best schemata which may belong to the optimal solution. The characters of chaos as well as advanced operators and parameter settings can improve both exploration and exploitation capacities of the algorithm. The results of multimodal function optimization show that CHGA performs simple genetic algorithms and effectively alleviates the problem of premature convergence.展开更多
Greenhouse system (GHS) is the worldwide fastest growing phenomenon in agricultural sector. Greenhouse models are essential for improving control efficiencies. The Relative Gain Analysis (RGA) reveals that the GHS con...Greenhouse system (GHS) is the worldwide fastest growing phenomenon in agricultural sector. Greenhouse models are essential for improving control efficiencies. The Relative Gain Analysis (RGA) reveals that the GHS control is complex due to 1) high nonlinear interactions between the biological subsystem and the physical subsystem and 2) strong coupling between the process variables such as temperature and humidity. In this paper, a decoupled linear cooling model has been developed using a feedback-feed forward linearization technique. Further, based on the model developed Internal Model Control (IMC) based Proportional Integrator (PI) controller parameters are optimized using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to achieve minimum Integral Square Error (ISE). The closed loop control is carried out using the above control schemes for set-point change and disturbance rejection. Finally, closed loop servo and servo-regulatory responses of GHS are compared quantitatively as well as qualitatively. The results implicate that IMC based PI controller using PSO provides better performance than the IMC based PI controller using GA. Also, it is observed that the disturbance introduced in one loop will not affect the other loop due to feedback-feed forward linearization and decoupling. Such a control scheme used for GHS would result in better yield in production of crops such as tomato, lettuce and broccoli.展开更多
Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper. This algorithm is more effective in global search while kee...Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper. This algorithm is more effective in global search while keeping the overall population size constant. The simulation results of function optimization show that with the proposed algorithm, the phenomenon of premature convergence can be overcome effectively, and a satisfying optimization result is obtained.展开更多
The identification and characteristics of premature convergence in genetic algorithms (GAs) are investigated Through a detailed quantitative analysis on the search capability and the degree of population diversity, th...The identification and characteristics of premature convergence in genetic algorithms (GAs) are investigated Through a detailed quantitative analysis on the search capability and the degree of population diversity, the cause of premature convergence in GAs is recognized, and attributed to the maturation effect of the GAs: The minimum schema deduced from current population, which is the largest search space of a GA, converges to a homogeneous population in probability 1 ( so the search capability of the GA decreases and premature convergence occurs). It is shown that, as quantitative features of the maturation effect, the degree of population diversity converges to zero with probability 1, and the tendency for premature convergence is inversely proportional to the population size and directly proportional to the variance of the fitness ratio of zero allele at any gene position of the current population. Based on the theoretical analysis, several strategies for preventing premature convergence are suggested A specific GA formulation that converges assuredly to the global optimum without appearance of premature convergence is proposed.展开更多
文摘With its wide use in different fields, the problem of the convergence of simple genetic algorithms (GAs) has been concerned. In the past, the research on the convergence of GAs was based on Holland's model theorem. The diversity of the evolutionary population and the convergence of GAs are studied by using the concept of negentropy based on the discussion of the characteristic of GA. Some test functions are used to test the convergence of GAs, and good results have been obtained. It is shown that the global optimization may be obtained by selecting appropriate parameters of simple GAs if the evolution time is enough.
文摘Enlightened by distribution of creatures in natural ecology environment, the distributionpopulation-based genetic algorithm (DPGA) is presented in this paper. The searching capability ofthe algorithm is improved by competition between distribution populations to reduce the search zone.This method is applied to design of optimal parameters of PID controllers with examples, and thesimulation results show that satisfactory performances are obtained.
基金funded by Shanghai Municipal Key Task Projects of Prospering Agriculture by Science and Technology Plan in China (Grant No. Hu Nong Ke Gong Zi 2008: 2-1)
文摘Weedy rice exerts a severe impact on rice production by competing for sunlight, water and nutrients. This study assayed the population structure, genetic diversity and origin of Northeast Asia weedy rice by using 48 simple sequence repeat markers. The results showed that weedy rice in Northeast Asia had a high genetic diversity, with Shannon＇s diversity index （I） of 0.748 and the heterozygosity （He） of 0.434. In each regional population, I value varied widely. The widest range of I （0.228-0.489） was observed in the weedy rice of Eastern China, which was larger than that of Northeast China and Korea （0.168-0.270）. The F-statistics of regional populations （Fis, Fit and Fst） also showed higher values in the weedy rice of Eastern China than those of Northeast China and Korea All weedy rice accessions were grouped into two clusters in the unweighted pair group method with arithmetic mean cluster analysis dendrogram, namely Eastern China branch and Northeastern China plus Korea branch. There was significant differentiation in genetic characteristics in weedy rice of northeastern and eastern Asia, especially in Eastern China.
基金Project supported by the LEB Research LaboratoryDepartment of Electrical Engineering,University of Batna 2, Algeria。
文摘The direct torque control of the dual star induction motor(DTC-DSIM) using conventional PI controllers is characterized by unsatisfactory performance, such as high ripples of torque and flux, and sensitivity to parametric variations. Among the most evoked control strategies adopted in this field to overcome these drawbacks presented in classical drive, it is worth mentioning the use of the second order sliding mode control(SOSMC) based on the super twisting algorithm(STA) combined with the fuzzy logic control(FSOSMC). In order to realize the optimal control performance, the FSOSMC parameters are adjusted using an optimization algorithm based on the genetic algorithm(GA). The performances of the envisaged control scheme, called G-FSOSMC, are investigated against G-SOSMC, G-PI and BBO-FSOSMC algorithms. The proposed controller scheme is efficient in reducing the torque and flux ripples, and successfully suppresses chattering. The effects of parametric uncertainties do not affect system performance.
基金Supported by the National Natural Science Foundation of China(No. 31061160187)Special Fund for Agro-scientific Research in the Public Interest (No. 200903005)Ocean University of China Students Innovation Trainning Program
文摘To investigate the genetic variation and population structure of Pacific herring in the Yellow Sea and the genetic differentiation between the Yellow Sea and the Sea of Japan, fragments of 479-bp mitochondrial DNA control region were sequenced for 110 individuals collected from three different periods in the Yellow Sea and one locality in the Sea of Japan. High haplotype diversity and moderate nucleotide diversity were observed in Pacific herring. AMOVA and exact test of population differentiation showed no significant genetic differentiations among the three populations of the Yellow Sea and suggested the populations can be treated as a single panmictic stock in the Yellow Sea. However, a large and significant genetic differentiation （ФST=0.11; P=0.00） was detected between the populations in the Yellow Sea and the Sea of Japan. The high sea water temperature in the Tsushima Strait was thought a barrier to block the gene exchange between populations of the two sea areas. The neutrality tests and mismatch distribution indicated recent population expansion in Pacific herring.
基金The National Natural Science Foundation of China !(No .699740 43 )
文摘An improved genetic algorithm (GA) is proposed based on the analysis of population diversity within the framework of Markov chain. The chaos operator to combat premature convergence concerning two goals of maintaining diversity in the population and sustaining the convergence capacity of the GA is introduced. In the CHaos Genetic Algorithm (CHGA), the population is recycled dynamically whereas the most highly fit chromosome is intact so as to restore diversity and reserve the best schemata which may belong to the optimal solution. The characters of chaos as well as advanced operators and parameter settings can improve both exploration and exploitation capacities of the algorithm. The results of multimodal function optimization show that CHGA performs simple genetic algorithms and effectively alleviates the problem of premature convergence.
文摘Greenhouse system (GHS) is the worldwide fastest growing phenomenon in agricultural sector. Greenhouse models are essential for improving control efficiencies. The Relative Gain Analysis (RGA) reveals that the GHS control is complex due to 1) high nonlinear interactions between the biological subsystem and the physical subsystem and 2) strong coupling between the process variables such as temperature and humidity. In this paper, a decoupled linear cooling model has been developed using a feedback-feed forward linearization technique. Further, based on the model developed Internal Model Control (IMC) based Proportional Integrator (PI) controller parameters are optimized using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to achieve minimum Integral Square Error (ISE). The closed loop control is carried out using the above control schemes for set-point change and disturbance rejection. Finally, closed loop servo and servo-regulatory responses of GHS are compared quantitatively as well as qualitatively. The results implicate that IMC based PI controller using PSO provides better performance than the IMC based PI controller using GA. Also, it is observed that the disturbance introduced in one loop will not affect the other loop due to feedback-feed forward linearization and decoupling. Such a control scheme used for GHS would result in better yield in production of crops such as tomato, lettuce and broccoli.
基金Supported by Basic Research Foundation of National Defence (No. B0203-031)
文摘Multiple genetic algorithms (GAs) need a large population size, which will take a long time for evolution. A new fuzzy adaptive GA is proposed in this paper. This algorithm is more effective in global search while keeping the overall population size constant. The simulation results of function optimization show that with the proposed algorithm, the phenomenon of premature convergence can be overcome effectively, and a satisfying optimization result is obtained.
基金Project supported by the National Natural Science Foundation of China.
文摘The identification and characteristics of premature convergence in genetic algorithms (GAs) are investigated Through a detailed quantitative analysis on the search capability and the degree of population diversity, the cause of premature convergence in GAs is recognized, and attributed to the maturation effect of the GAs: The minimum schema deduced from current population, which is the largest search space of a GA, converges to a homogeneous population in probability 1 ( so the search capability of the GA decreases and premature convergence occurs). It is shown that, as quantitative features of the maturation effect, the degree of population diversity converges to zero with probability 1, and the tendency for premature convergence is inversely proportional to the population size and directly proportional to the variance of the fitness ratio of zero allele at any gene position of the current population. Based on the theoretical analysis, several strategies for preventing premature convergence are suggested A specific GA formulation that converges assuredly to the global optimum without appearance of premature convergence is proposed.
