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| 1 | Frequency modulated weak signal detection based on stochastic resonance and genetic algorithm显示文摘Stochastic resonance system is subject to the restriction of small frequency parameter in weak signal detection,in order to solve this problem,a frequency modulated weak signal detection method based on stochastic resonance and genetic algorithm is presented in this paper. The frequency limit of stochastic resonance is eliminated by introducing carrier signal,which is multiplied with the measured signal to be injected in the stochastic resonance system,meanwhile,using genetic algorithm to optimize the carrier signal frequency,which determine the generated difference-frequency signal in the lowfrequency range,so as to achieve the stochastic resonance weak signal detection. Results showthat the proposed method is feasible and effective,which can significantly improve the output SNR of stochastic resonance,in addition,the system has the better self-adaptability,according to the operation result and output phenomenon,the unknown frequency of the signal to be measured can be obtained,so as to realize the weak signal detection of arbitrary frequency. | XING Hongyan LU Chunxia ZHANG Qiang | 2016 | Instrumentation2016，3，1： | 16 |
| 2 | 基于遗传算法的中国清洁能源需求Logistic预测模型显示文摘通过分析中国历年能源需求量变化规律,得出序列近10 a增长趋势与以往明显不同。为准确描述能源需求增长趋势,用整体序列和近10 a序列分别建立Logistic模型,再将两者耦合,并运用遗传算法优化模型参数,由此建立基于遗传算法的能源需求Logistic中长期预测模型。运用该模型对中国2020年能源需求量进行预测,并构建未来社会经济发展情景,结合碳减排目标推求清洁能源需求量,由此建立基于遗传算法的清洁能源Logistic中长期预测模型,并对中国2020年清洁能源需求量进行预测分析。结果表明,该模型物理概念明确,思路清晰,预测结果与中国能源规划目标相符,具有一定的合理性。 | 付娟 金菊良 魏一鸣 蒋尚明 | 2010 | 水电能源科学2010，28，9： | 12 |
| 3 | A Linear Domain System Identification for Small Unmanned Aerial Rotorcraft Based on Adaptive Genetic Algorithm显示文摘This paper proposes a new adaptive linear domain system identification method for small unmanned aerial rotorcraft.Byusing the flash memory integrated into the micro guide navigation control module, system records the data sequences of flighttests as inputs (control signals for servos) and outputs (aircraft’s attitude and velocity information).After data preprocessing, thesystem constructs the horizontal and vertical dynamic model for the small unmanned aerial rotorcraft using adaptive geneticalgorithm.The identified model is verified by a series of simulations and tests.Comparison between flight data and the one-stepprediction data obtained from the identification model shows that the dynamic model has a good estimation for real unmannedaerial rotorcraft system.Based on the proposed dynamic model, the small unmanned aerial rotorcraft can perform hovering,turning, and straight flight tasks in real flight tests. | Xusheng Lei,Yuhu Du School of the Instrumentation Science and Opto-Electronic Engineering,Beihang University,Beijing 100191,P.R.China | 2010 | Journal of Bionic Engineering2010，7，2： | 12 |
| 4 | 基于广义相关系数自适应随机共振的液压泵振动信号预处理方法显示文摘针对液压泵故障振动信号信噪比低,故障特征难以提取的问题,对液压泵振动信号预处理方法进行研究。针对现有自适应随机共振优化算法及其目标函数存在的问题,将量子遗传算法(Quantum Genetic Algorithm,QGA)引入自适应随机共振中,提出一种改进的自适应随机共振的信号预处理方法。该方法以广义相关系数为目标函数,采用QGA算法对随机共振系统的结构参数进行优化,从而实现对信号的降噪预处理。仿真及实验结果表明,该方法能够有效提取强噪声背景下的液压泵振动信号频率特征,是液压泵故障特征提取及故障诊断中信号预处理的有效方法,可进一步发展至实际工程应用。 | 经哲 郭利 | 2016 | 振动与冲击2016，35，16： | 11 |
| 5 | Parameters selection in gene selection using Gaussian kernel support vector machines by genetic algorithm显示文摘In microarray-based cancer classification, gene selection is an important issue owing to the large number of variables and small number of samples as well as its non-linearity. It is difficult to get satisfying results by using conventional linear sta- tistical methods. Recursive feature elimination based on support vector machine (SVM RFE) is an effective algorithm for gene selection and cancer classification, which are integrated into a consistent framework. In this paper, we propose a new method to select parameters of the aforementioned algorithm implemented with Gaussian kernel SVMs as better alternatives to the common practice of selecting the apparently best parameters by using a genetic algorithm to search for a couple of optimal parameter. Fast implementation issues for this method are also discussed for pragmatic reasons. The proposed method was tested on two repre- sentative hereditary breast cancer and acute leukaemia datasets. The experimental results indicate that the proposed method per- forms well in selecting genes and achieves high classification accuracies with these genes. | 毛勇 周晓波 皮道映 孙优贤 WONG Stephen T.C. | 2005 | Journal of Zhejiang University-Science B(Biomedicine & Biotechnology)2005，6，10： | 11 |
| 6 | A Decision Support Method for Truck Scheduling and Storage Allocation Problem at Container显示文摘Truck scheduling and storage allocation, as two separate subproblems in port operations, have been deeply studied in past decades. However, from the operational point of view, they are highly interdependent. Storage allocation for import containers has to balance the travel time and queuing time of each container in yard. This paper proposed an integer programming model handling these two problems as a whole. The objective of this model is to reduce congestion and waiting time of container trucks in the terminal so as to decrease the makespan of discharging containers. Due to the inherent complexity of the prob-lem, a genetic algorithm and a greedy heuristic algorithm are designed to attain near optimal solutions. It shows that the heuristic algorithm can achieve the optimal solution for small-scale problems. The solutions of small-and large-scale problems obtained from the heuristic algorithm are better than those from the genetic algorithm. | 曹瑾鑫 史其信 Der-Horng Lee | 2008 | Tsinghua Science and Technology2008，13，S1： | 10 |
| 7 | Adaptive Resources Allocation Algorithm Based on Modified PSO for Cognitive Radio System显示文摘Radio spectrum has become a rare resource due to the rapid development of wireless communication technique. Cognitive radio is one of important techniques to deal with this radio spectrum problem. But the resource allocation in cognitive radio also has its own issues, such as the flexibility of the allocation algorithm, the performance of resource allocation, and so on. In order to increase the flexibility of the allocation algorithm for cognitive radio, more and more researches are focusing on the evolutionary algorithms, such as genetic algorithm(GA), particle swarm optimization(PSO). Evolutionary algorithm can greatly improve the flexibility of the allocation algorithm for cognitive radio system in different communication scenarios, but the performances are relatively lower than the original mathematical methods. So in this paper, we proposed an adaptive resource allocation algorithm based on modified PSO for cognitive radio system to solve these problems. Modified particle swarm optimization(Modified PSO) has both genetic algorithm(GA) and particle swarm optimization(PSO)’s updating processes which makes this modified PSO overcame PSO’s own disadvantages and keep advantages. Simulation results showed our proposed algorithm has enough flexibility to meet cognitive radio systems’ requirements, and also has a better performance than original PSO. | Yi Yang Qinyu Zhang Ye Wang Takahiro Emoto Masatake Akutagawa Shinsuke Konaka | 2019 | China Communications2019，16，5： | 9 |
| 8 | Origin of tectonic stresses in the Chinese continent and adjacent areas显示文摘Based on data of principal stress orientation from focal mechanism and of geological features in China, we made pseudo-3D genetic algorithm finite element (GA-FEM) inversion to investigate the main forces acting on the Chinese continent and adjacent areas which form the Chinese tectonic stress field. The results confirm that plate boundary forces play the dominant role in forming the stress field in China, as noticed by many previous researchers. However, we also find that topographic spreading forces, as well as basal drag forces of the lower crust to the upper crust, make significant contribution to stresses in regional scale. Forces acting on the Chinese continent can be outlined as follows: the collision of the India plate to the NNE is the most important action, whereby forces oriented to the NW by the Philippine plate and forces oriented to the SWW by the Pacific plate are also important. Topographic spreading forces are not negligible at high topographic gradient zones, these forces are perpendicular to edges of the Tibetan Plateau and a topographic gradient belt running in the NNE direction across Eastern China. Basal drag forces applied by the ductile flow of the lower crust to the base of upper crust affect the regional stress field in the Tibetan Plateau remarkably, producing the clockwise rotation around the eastern Himalaya syntax. | ZHU ShouBiao1,2& SHI YaoLin3 1 Institute of Crustal Dynamics, China Earthquake Administration, Beijing 100085, China 2 Department of Geophysics, Peking University, Beijing 100871, China 3 Laboratory of Computational Geodynamics, Graduate University of Chinese Academy of Sciences, Beijing 100049, China | 2007 | Science China Earth Sciences2007，50，1： | 9 |
| 9 | Genetic Algorithm Based on New Evaluation Function and Mutation Model for Training of BPNN显示文摘A local minimum is frequently encountered in the training of back propagation neural networks (BPNN), which sharply slows the training process. In this paper, an analysis of the formation of local minima is presented, and an improved genetic algorithm (GA) is introduced to overcome local minima. The Sigmoid function is generally used as the activation function of BPNN nodes. It is the flat characteristic of the Sigmoid function that results in the formation of local minima. In the improved GA, pertinent modifications are made to the evaluation function and the mutation model. The evaluation of the solution is associated with both the training error and gradient. The sensitivity of the error function to network parameters is used to form a self adapting mutation model. An example of industrial application shows the advantage of the improved GA to overcome local minima. | 周祥 何小荣 陈丙珍 | 2002 | Tsinghua Science and Technology2002，7，1： | 8 |
| 10 | A Hybrid Time-delay Prediction Method for Networked Control System显示文摘This paper presents an Ethernet based hybrid method for predicting random time-delay in the networked control system.First,db3 wavelet is used to decompose and reconstruct time-delay sequence,and the approximation component and detail components of time-delay sequences are fgured out.Next,one step prediction of time-delay is obtained through echo state network(ESN)model and auto-regressive integrated moving average model(ARIMA)according to the diferent characteristics of approximate component and detail components.Then,the fnal predictive value of time-delay is obtained by summation.Meanwhile,the parameters of echo state network is optimized by genetic algorithm.The simulation results indicate that higher accuracy can be achieved through this prediction method. | Zhong-Da Tian Xian-Wen Gao Kun Li | 2014 | International Journal of Automation and computing2014，11，1： | 8 |
| 11 | Neural Network Based on GA-BP Algorithm and its Application in the Protein Secondary Structure Prediction显示文摘The advantages and disadvantages of genetic algorithm and BP algorithm are introduced. A neural network based on GA-BP algorithm is proposed and applied in the prediction of protein secondary structure, which combines the advantages of BP and GA. The prediction and training on the neural network are made respectively based on 4 structure classifications of protein so as to get higher rate of predication---the highest prediction rate 75.65%,the average prediction rate 65.04%. | YANG Yang LI Kai-yang | 2006 | Chinese Journal of Biomedical Engineering(English Edition)2006，15，1： | 8 |
| 12 | Fuzzy-GA PID controller with incomplete derivation and its application to intelligent bionic artificial leg显示文摘An optimal PID controller with incomplete derivation is proposed based on fuzzy inference and the geneticalgorithm, which is called the fuzzy-GA PID controller with incomplete derivation. It consists of the off-line part andthe on-line part. In the off-line part, by taking the overshoot, rise time, and settling time of system unit step re-sponse as the performance indexes and by using the genetic algorithm, a group of optimal PID parameters K*p , Ti* ,and Tj are obtained, which are used as the initial values for the on-line tuning of PID parameters. In the on-linepart, based on K; , Ti* , and T*d and according to the current system error e and its time derivative, a dedicatedprogram is written, which is used to optimize and adjust the PID parameters on line through a fuzzy inference mech-anism to ensure that the system response has optimal dynamic and steady-state performance. The controller has beenused to control the D. C. motor of the intelligent bionic artificial leg designed by the authors. The result of computersimulation shows that this kind of optimal PID controller has excellent control performance and robust performance. | 谭冠政 李安平 | 2003 | Journal of Central South University of Technology2003，10，3： | 8 |
| 13 | A Novel Genetic Algorithm Preventing Premature Convergence by Chaos Operator显示文摘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. | LIU Juan CAI Zi-xing LIU Jian-qin | 2000 | Journal of Central South University2000，12，2： | 8 |
| 14 | 多目标遗传算法NSGA-Ⅱ在某双前桥转向机构优化设计中的应用显示文摘针对东风某双前桥转向重型汽车在使用中存在的轮胎异常磨损问题,利用ADAMS/View软件建立了样车双前桥转向机构参数化仿真模型,基于选择的设计变量与目标函数,在iSIGHT软件中通过集成ADAMS/View模型,对设计变量进行了DOE分析,并利用改进的非支配排序遗传算法NSGA-Ⅱ实现了双前桥转向机构的多目标优化,根据Pareto最优解得到仿真结果表明:优化后各车轮转角误差大大减小,可有效解决车轮异常磨损问题。利用多目标遗传算法和计算机仿真集成技术对转向机构进行优化设计,可为今后汽车系统的设计、开发提供新的有效途径。 | 周红妮 冯樱 胡群 赵慧勇 | 2015 | 机械设计与制造2015，，11： | 7 |
| 15 | A Gene-Pool Based Genetic Algorithm for TSP显示文摘Based on the analysis of previous genetic algorithms (GAs) for TSP, a novel method called Ge- GA is proposed. It combines gene pool and GA so as to direct the evolution of the whole population. The core of Ge- GA is the construction of gene pool and how to apply it to GA. Different from standard GAs, Ge- GA aims to enhance the ability of exploration and exploitation by incorporating global search with local search. On one hand a local search called Ge- Lo-calSearch operator is proposed to improve the solution quality, on the other hand the modified Inver-Over operator called Ge InverOver is considered as a global search mechanism to expand solution space of local minimal. Both of these operators are based on the gene pool. Our algorithm is applied to 11 well-known traveling salesman problems whose numbers of cities are from 70 to 1577 cities. The experiments results indicate that Ge- GA has great robustness for TSP. For each test instance, the average value of solution quality, found in accepted time, | Yang Hui, Kang Li-shan, Chen Yu-pingState Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, Hubei, China | 2003 | Wuhan University Journal of Natural Sciences2003，8，S1： | 6 |
| 16 | Self-adaptive PID controller of microwave drying rotary device tuning on-line by genetic algorithms显示文摘The control design, based on self-adaptive PID with genetic algorithms(GA) tuning on-line was investigated, for the temperature control of industrial microwave drying rotary device with the multi-layer(IMDRDWM) and with multivariable nonlinear interaction of microwave and materials. The conventional PID control strategy incorporated with optimization GA was put forward to maintain the optimum drying temperature in order to keep the moisture content below 1%, whose adaptation ability included the cost function of optimization GA according to the output change. Simulations on five different industrial process models and practical temperature process control system for selenium-enriched slag drying intensively by using IMDRDWM were carried out systematically, indicating the reliability and effectiveness of control design. The parameters of proposed control design are all on-line implemented without iterative predictive calculations, and the closed-loop system stability is guaranteed, which makes the developed scheme simpler in its synthesis and application, providing the practical guidelines for the control implementation and the parameter design. | 杨彪 梁贵安 彭金辉 郭胜惠 李玮 张世敏 李英伟 白松 | 2013 | Journal of Central South University2013，20，10： | 6 |
| 17 | Numerical simulation and optimized design of cased telescoped ammunition interior ballistic显示文摘In order to achieve the optimized design of a cased telescoped ammunition(CTA) interior ballistic design,a genetic algorithm was introduced into the optimal design of CTA interior ballistics with coupling the CTA interior ballistic model. Aiming at the interior ballistic characteristics of a CTA gun, the goal of CTA interior ballistic design is to obtain a projectile velocity as large as possible. The optimal design of CTA interior ballistic is carried out using a genetic algorithm by setting peak pressure, changing the chamber volume and gun powder charge density. A numerical simulation of interior ballistics based on a 35 mm CTA firing experimental scheme was conducted and then the genetic algorithm was used for numerical optimization. The projectile muzzle velocity of the optimized scheme is increased from 1168 m/s for the initial experimental scheme to 1182 m/s. Then four optimization schemes were obtained with several independent optimization processes. The schemes were compared with each other and the difference between these schemes is small. The peak pressure and muzzle velocity of these schemes are almost the same. The result shows that the genetic algorithm is effective in the optimal design of the CTA interior ballistics. This work will be lay the foundation for further CTA interior ballistic design. | Jia-gang Wang Yong-gang Yu Liang-liang Zhou Rui Ye | 2018 | Defence Technology(防务技术)2018，14，2： | 6 |
| 18 | Non-smooth environment modeling and global path planning for mobile robots显示文摘An Approximate Voronoi Boundary Network is constructed as the environmental model by way of enlar-ging the obstacle raster. The connectivity of the path network under complex environment is ensured through build-ing the second order Approximate Voronoi Boundary Network after adding virtual obstacles at joint-close grids. Thismethod embodies the network structure of the free area of environment with less nodes, so the complexity of pathplanning problem is reduced largely. An optimized path for mobile robot under complex environment is obtainedthrough the Genetic Algorithm based on the elitist rule and re-optimized by using the path-tightening method. Sincethe elitist one has the only authority of crossover, the management of one group becomes simple, which makes forobtaining the optimized path quickly. The Approximate Voronoi Boundary Network has a good tolerance to the im-precise a priori information and the noises of sensors under complex environment. Especially it is robust in dealingwith the local or partial changes, so a small quantity of dynamic obstacles is difficult to alter the overall character ofits connectivity, which means that it can also be adopted in dynamic environment by fusing the local path planning. | 邹小兵 蔡自兴 孙国荣 | 2003 | Journal of Central South University of Technology2003，10，3： | 6 |
| 19 | A Hybrid Genetic Algorithm for Reduct of Attributes in Decision System Based on Rough Set Theory显示文摘Knowledge reduction is an important issue when dealing with huge amounts of data. And it has been proved that computing the minimal reduct of decision system is NP\|complete. By introducing heuristic information into genetic algorithm, we proposed a heuristic genetic algorithm. In the genetic algorithm, we constructed a new operator to maintaining the classification ability. The experiment shows that our algorithm is efficient and effective for minimal reduct, even for the special example that the simple heuristic algorithm can’t get the right result. | Dai Jian\|hua 1,2 , Li Yuan\|xiang 1,2 ,Liu Qun 3 1. State Key Laboratory of Software Engineering, Wuhan University, Wuhan 430072, Hubei,China 2. School of Computer, Wuhan University, Wuhan 430072, Hubei, China 3. School of Computer Science, | 2002 | Wuhan University Journal of Natural Sciences2002，7，3： | 6 |
| 20 | Fuzzy cost-profit tradeoff model for locating a vehicle inspection station considering regional constraints显示文摘Facility location allocation(FLA) is one of the important issues in the logistics and transportation fields. In practice, since customer demands, allocations, and even locations of customers and facilities are usually changing, the FLA problem features uncertainty. To account for this uncertainty, some researchers have addressed the fuzzy profit and cost issues of FLA. However, a decision-maker needs to reach a specific profit, minimizing the cost to target customers. To handle this issue it is essential to propose an effective fuzzy cost-profit tradeoff approach of FLA. Moreover, some regional constraints can greatly influence FLA. By taking a vehicle inspection station as a typical automotive service enterprise example, and combined with the credibility measure of fuzzy set theory, this work presents new fuzzy cost-profit tradeoff FLA models with regional constraints. A hybrid algorithm integrating fuzzy simulation and genetic algorithms(GA) is proposed to solve the proposed models. Some numerical examples are given to illustrate the proposed models and the effectiveness of the proposed algorithm. | Guangdong TIAN Hua KE Xiaowei CHEN | 2014 | Journal of Zhejiang University-Science C(Computers and Electronics)2014，15，12： | 5 |
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