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小产权房适法化探析
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作者 姜瑜 《邢台学院学报》 2012年第3期44-45,共2页
小产权房也能够获得国有土地证的事实在警示我们,我国目前关于小产权房的立法空白和错位已经到了亟待纠正的地步。应建立健全以《物权法》为核心的集体土地管理的法律体系,并通过多种途径逐步放开集体土地以及小产权房的市场准入。
关键词 小产权房 适法化 宅基地使用权
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A Filtering Approach Based on MMAE for a SINS/CNS Integrated Navigation System 被引量:9
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作者 Fangfang Zhao Cuiqiao Chen +1 位作者 Wei He Shuzhi Sam Ge 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2018年第6期1113-1120,共8页
This paper explores multiple model adaptive estimation(MMAE) method, and with it, proposes a novel filtering algorithm. The proposed algorithm is an improved Kalman filter— multiple model adaptive estimation unscente... This paper explores multiple model adaptive estimation(MMAE) method, and with it, proposes a novel filtering algorithm. The proposed algorithm is an improved Kalman filter— multiple model adaptive estimation unscented Kalman filter(MMAE-UKF) rather than conventional Kalman filter methods,like the extended Kalman filter(EKF) and the unscented Kalman filter(UKF). UKF is used as a subfilter to obtain the system state estimate in the MMAE method. Single model filter has poor adaptability with uncertain or unknown system parameters,which the improved filtering method can overcome. Meanwhile,this algorithm is used for integrated navigation system of strapdown inertial navigation system(SINS) and celestial navigation system(CNS) by a ballistic missile's motion. The simulation results indicate that the proposed filtering algorithm has better navigation precision, can achieve optimal estimation of system state, and can be more flexible at the cost of increased computational burden. 展开更多
关键词 Celestial navigation integrated navigation multiple model adaptive estimation unscented Kalman filter (MMAEUKF) strap-down inertial navigation
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Adaptive Immune Evolutionary Algorithms Based on Immune Network Regulatory Mechanism 被引量:3
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作者 何宏 钱锋 《Journal of Donghua University(English Edition)》 EI CAS 2007年第1期141-145,共5页
Based on immune network regulatory mechanism, a new adaptive immune evolutionary algorithm (AIEA) is proposed to improve the performance of genetic algorithms (GA) in this paper. AIEA adopts novel selection operation ... Based on immune network regulatory mechanism, a new adaptive immune evolutionary algorithm (AIEA) is proposed to improve the performance of genetic algorithms (GA) in this paper. AIEA adopts novel selection operation according to the stimulation level of each antibody. A memory base for good antibodies is devised simultaneously to raise the convergent rapidity of the algorithm and adaptive adjusting strategy of antibody population is used for preventing the loss of the population adversity. The experiments show AIEA has better convergence performance than standard genetic algorithm and is capable of maintaining the adversity of the population and solving function optimization problems in an efficient and reliable way. 展开更多
关键词 evolutionary algorithm immune network ADAPTATION stimulation level.
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Estimation of Kinetic Parameters for Autocatalytic Oxidation of Cyclohexane Based on a Modified Adaptive Genetic Algorithm 被引量:2
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作者 刘平乐 邹丽珊 +2 位作者 罗和安 王良芥 郑金华 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2004年第1期49-54,共6页
A modified genetic algorithm of multiple selection strategies, crossover strategies and adaptive operator is constructed, and it is used to estimate the kinetic parameters in autocatalytic oxidation of cyclohexane. Th... A modified genetic algorithm of multiple selection strategies, crossover strategies and adaptive operator is constructed, and it is used to estimate the kinetic parameters in autocatalytic oxidation of cyclohexane. The influences of selection strategy, crossover strategy and mutation strategy on algorithm performance are discussed. This algorithm with a specially designed adaptive operator avoids the problem of local optimum usually associated with using standard genetic algorithm and simplex method. The kinetic parameters obtained from the modified genetic algorithm are credible and the calculation results using these parameters agree well with experimental data. Furthermore, a new kinetic model of cyclohexane autocatalytic oxidation is established and the kinetic parameters are estimated by using the modified genetic algorithm. 展开更多
关键词 adaptive genetic algorithm CYCLOHEXANE autocatalytic oxidation reaction kinetics
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An Immune Self-adaptive Differential Evolution Algorithm with Application to Estimate Kinetic Parameters for Homogeneous Mercury Oxidation 被引量:12
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作者 胡春平 颜学峰 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2009年第2期232-240,共9页
A new version of differential evolution (DE) algorithm, in which immune concepts and methods are applied to determine the parameter setting, named immune self-adaptive differential evolution (ISDE), is proposed to... A new version of differential evolution (DE) algorithm, in which immune concepts and methods are applied to determine the parameter setting, named immune self-adaptive differential evolution (ISDE), is proposed to improve the performance of the DE algorithm. During the actual operation, ISDE seeks the optimal parameters arising from the evolutionary process, which enable ISDE to alter the algorithm for different optimization problems and improve the performance of ISDE by the control parameters' self-adaptation. The .performance of the proposed method is studied with the use of nine benchmark problems and compared with original DE algorithm ~nd-other well-known self-adaptive DE algorithms. The experiments conducted show that the ISDE clearly outperforms the other DE algorithms in all benchmark functions. Furthermore, ISDE is applied to develop the kinetic model for homogeneous mercury. (Hg) oxidation in flue gas, and satisfactory results are obtained. 展开更多
关键词 differential evolution immune system evolutionary computation parameter estimation
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Multi-objective optimization of p-xylene oxidation process using an improved self-adaptive differential evolution algorithm 被引量:1
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作者 Lili Tao Bin Xu +1 位作者 Zhihua Hu Weimin Zhong 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2017年第8期983-991,共9页
The rise in the use of global polyester fiber contributed to strong demand of the Terephthalic acid (TPA). The liquid-phase catalytic oxidation of p-xylene (PX) to TPA is regarded as a critical and efficient chemi... The rise in the use of global polyester fiber contributed to strong demand of the Terephthalic acid (TPA). The liquid-phase catalytic oxidation of p-xylene (PX) to TPA is regarded as a critical and efficient chemical process in industry [ 1 ]. PX oxidation reaction involves many complex side reactions, among which acetic acid combustion and PX combustion are the most important. As the target product of this oxidation process, the quality and yield of TPA are of great concern. However, the improvement of the qualified product yield can bring about the high energy consumption, which means that the economic objectives of this process cannot be achieved simulta- neously because the two objectives are in conflict with each other. In this paper, an improved self-adaptive multi-objective differential evolution algorithm was proposed to handle the multi-objective optimization prob- lems. The immune concept is introduced to the self-adaptive multi-objective differential evolution algorithm (SADE) to strengthen the local search ability and optimization accuracy. The proposed algorithm is successfully tested on several benchmark test problems, and the performance measures such as convergence and divergence metrics are calculated. Subsequently, the multi-objective optimization of an industrial PX oxidation process is carried out using the proposed immune self-adaptive multi-objective differential evolution algorithm (ISADE). Optimization results indicate that application oflSADE can greatly improve the yield of TPA with low combustion loss without degenerating TA quality. 展开更多
关键词 p-Xylene oxidation Operation condition optimization Multi-objective optimization Self-adaptive differential evolution
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Adaptive Optimal Capacity Perception and Control for Wireless Multi-Hop Networks 被引量:1
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作者 Zhao Haitao Dong Yuning +2 位作者 Liu Nanjie Zhang Hui Tian Feng 《China Communications》 SCIE CSCD 2012年第11期23-30,共8页
In wireless multimedia communications, it is extremely difficult to derive general end-to-end capacity results because of decentralized packet scheduling and the interference between communicating nodes. In this paper... In wireless multimedia communications, it is extremely difficult to derive general end-to-end capacity results because of decentralized packet scheduling and the interference between communicating nodes. In this paper, we present a state-based channel capacity perception scheme to provide statistical Quality-of-Service (QoS) guarantees under a medium or high traffic load for IEEE 802.11 wireless multi-hop networks. The proposed scheme first perceives the state of the wireless link from the MAC retransmission information and extends this information to calculate the wireless channel capacity, particularly under a saturated traffic load, on the basis of the interference among flows and the link state in the wireless multi-hop networks. Finally, the adaptive optimal control algorithm allocates a network resource and forwards the data packet by taking into consideration the channel capacity deployments in multi-terminal or multi-hop mesh networks. Extensive computer simulations demonstrate that the proposed scheme can achieve better performance in terms of packet delivery ratio and network throughput compared to the existing capacity prediction schemes. 展开更多
关键词 wireless multi-hop networks capacity perception: statistical Quality of Service (QoS) CROSS-LAYER
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Composite multiobjective optimization beamforming based on genetic algorithms 被引量:1
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作者 史兢 Meng Weixiao Zhang Naitong Wang Zheng 《High Technology Letters》 EI CAS 2006年第3期283-287,共5页
All the parameters of beamforming are usually optimized simultaneously in implementing the optimization of antenna array pattern with multiple objectives and parameters by genetic algorithms (GAs). Firstly, this pap... All the parameters of beamforming are usually optimized simultaneously in implementing the optimization of antenna array pattern with multiple objectives and parameters by genetic algorithms (GAs). Firstly, this paper analyzes the performance of fitness functions of previous algorithms. It shows that original algorithms make the fitness functions too complex leading to large amount of calculation, and also the selection of the weight of parameters very sensitive due to many parameters optimized simultaneously. This paper proposes a kind of algorithm of composite beamforming, which detaches the antenna array into two parts corresponding to optimization of different objective parameters respectively. New algorithm substitutes the previous complex fitness function with two simpler functions. Both theoretical analysis and simulation results show that this method simplifies the selection of weighting parameters and reduces the complexity of calculation. Furthermore, the algorithm has better performance in lowering side lobe and interferences in comparison with conventional algorithms of beamforming in the case of slightly widening the main lobe. 展开更多
关键词 genetic algorithms composite beamforming fitness function
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Optimization Algorithm for Operation Comfortability of Master Manipulator of Minimally Invasive Surgery Robot 被引量:2
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作者 李进华 王雪生 +3 位作者 邢元 王树新 李建民 梁科 《Transactions of Tianjin University》 EI CAS 2016年第2期95-104,共10页
To evaluate the operation comfortability in the master-slave robotic minimally invasive surgery(MIS), an optimal function was built with two operation comfortability decided indices, i.e., the center distance and volu... To evaluate the operation comfortability in the master-slave robotic minimally invasive surgery(MIS), an optimal function was built with two operation comfortability decided indices, i.e., the center distance and volume contact ratio. Two verifying experiments on Phantom Desktop and Micro Hand S were conducted. Experimental results show that the operation effect at the optimal relative location is better than that at the random location, which means that the optimal function constructed in this paper is effective in optimizing the operation comfortability. 展开更多
关键词 MIS robot master manipulator operation comfortability Phantom Desktop Micro Hand S
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Capability Analysis of Chaotic Mutation and Its Self-Adaption
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作者 YANGLi-Jiang CHENTian-Lun 《Communications in Theoretical Physics》 SCIE CAS CSCD 2002年第5期555-560,共6页
Through studying several kinds of chaotic mappings' distributions of orbital points, we analyze the capability of the chaotic mutations based on these mappings. Numerical experiments support our conclusions very w... Through studying several kinds of chaotic mappings' distributions of orbital points, we analyze the capability of the chaotic mutations based on these mappings. Numerical experiments support our conclusions very well. The capability analysis also led to a self-adaptive mechanism of chaotic mutation. The introducing of the self-adaptive chaotic mutation can improve the performance of genetic algorithm very prominently. 展开更多
关键词 genetics algorithms chaotic mutation function optimization self-adaption
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A Grey Wolf Optimization-Based Tilt Tri-rotor UAV Altitude Control in Transition Mode 被引量:2
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作者 MA Yan WANG Yingxun +2 位作者 CAI Zhihao ZHAO Jiang LIU Ningjun 《Transactions of Nanjing University of Aeronautics and Astronautics》 EI CSCD 2022年第2期186-200,共15页
To solve the problem of altitude control of a tilt tri-rotor unmanned aerial vehicle(UAV)in the transition mode,this study presents a grey wolf optimization(GWO)based neural network adaptive control scheme for a tilt ... To solve the problem of altitude control of a tilt tri-rotor unmanned aerial vehicle(UAV)in the transition mode,this study presents a grey wolf optimization(GWO)based neural network adaptive control scheme for a tilt trirotor UAV in the transition mode.Firstly,the nonlinear model of the tilt tri-rotor UAV is established.Secondly,the tilt tri-rotor UAV altitude controller and attitude controller are designed by a neural network adaptive control method,and the GWO algorithm is adopted to optimize the parameters of the neural network and the controllers.Thirdly,two altitude control strategies are designed in the transition mode.Finally,comparative simulations are carried out to demonstrate the effectiveness and robustness of the proposed control scheme. 展开更多
关键词 tilt tri-rotor unmanned aerial vehicle altitude control neural network adaptive control grey wolf optimization(GWO)
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A novel adaptive mutative scale optimization algorithm based on chaos genetic method and its optimization efficiency evaluation 被引量:5
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作者 王禾军 鄂加强 邓飞其 《Journal of Central South University》 SCIE EI CAS 2012年第9期2554-2560,共7页
By combing the properties of chaos optimization method and genetic algorithm,an adaptive mutative scale chaos genetic algorithm(AMSCGA) was proposed by using one-dimensional iterative chaotic self-map with infinite co... By combing the properties of chaos optimization method and genetic algorithm,an adaptive mutative scale chaos genetic algorithm(AMSCGA) was proposed by using one-dimensional iterative chaotic self-map with infinite collapses within the finite region of [-1,1].Some measures in the optimization algorithm,such as adjusting the searching space of optimized variables continuously by using adaptive mutative scale method and making the most circle time as its control guideline,were taken to ensure its speediness and veracity in seeking the optimization process.The calculation examples about three testing functions reveal that AMSCGA has both high searching speed and high precision.Furthermore,the average truncated generations,the distribution entropy of truncated generations and the ratio of average inertia generations were used to evaluate the optimization efficiency of AMSCGA quantificationally.It is shown that the optimization efficiency of AMSCGA is higher than that of genetic algorithm. 展开更多
关键词 chaos genetic optimization algorithm CHAOS genetic algorithm optimization efficiency
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PSO-based Control Algorithm for Polarization Mode Dispersion Self-adaptive Compensation
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作者 ZHU Jin-jun ZHANG Xiao-guang +1 位作者 DUAN Gao-yan WANG Qiu-guo 《Semiconductor Photonics and Technology》 CAS 2006年第4期217-223,256,共8页
Polarization mode dispersion(PMD) is considered to be the ultimate limitation in high-speed optical fiber communication systems. Establishing an effective control algorithm for adaptive PMD compensation is a challengi... Polarization mode dispersion(PMD) is considered to be the ultimate limitation in high-speed optical fiber communication systems. Establishing an effective control algorithm for adaptive PMD compensation is a challenging task, because PMD possesses the time-varying and statistical properties. The particle swarm optimization(PSO) algorithm is introduced into self-adaptive PMD compensation as feedback control algorithm. The experiment results show that PSO-based control algorithm has some unique features of rapid convergence to the global optimum without being trapped in local sub-optima and good robustness to noise in the optical fiber transmission line that has never been achieved in PMD compensation before. 展开更多
关键词 Polarization mode dispersion Particle swarm optimization Self-adaptive compensation
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Convergence of shape optimization calculations of mechanical components using adaptive biological growth and iterative finite element methods 被引量:1
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作者 Mohammad Zehsaz Kaveh E.Torkanpouri Amin Paykani 《Journal of Central South University》 SCIE EI CAS 2013年第1期76-82,共7页
Shape optimization of mechanical components is one of the issues that have been considered in recent years. Different methods were presented such as adaptive biological for reducing costs and increasing accuracy. The ... Shape optimization of mechanical components is one of the issues that have been considered in recent years. Different methods were presented such as adaptive biological for reducing costs and increasing accuracy. The effects of step factor, the number of control points and the definition way of control points coordinates in convergence rate were studied. A code was written using ANSYS Parametric Design Language (APDL) which receives the studied parameters as input and obtains the optimum shape for the components. The results show that for achieving successful optimization, step factor should be in a specific range. It is found that the use of any coordinate system in defining control points coordinates and selection of any direction for stimulus vector of algorithm will also result in optimum shape. Furthermore, by increasing the number of control points, some non-uniformities are created in the studied boundary. Achieving acceptable accuracy seems impossible due to the creation of saw form at the studied boundary which is called "saw position". 展开更多
关键词 shape optimization adaptive biological growth control points step factor optimization rate
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An improved self-adaptive membrane computing optimization algorithm and its applications in residue hydrogenating model parameter estimation 被引量:1
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作者 芦会彬 薄翠梅 杨世品 《Journal of Central South University》 SCIE EI CAS CSCD 2015年第10期3909-3915,共7页
In order to solve the non-linear and high-dimensional optimization problems more effectively, an improved self-adaptive membrane computing(ISMC) optimization algorithm was proposed. The proposed ISMC algorithm applied... In order to solve the non-linear and high-dimensional optimization problems more effectively, an improved self-adaptive membrane computing(ISMC) optimization algorithm was proposed. The proposed ISMC algorithm applied improved self-adaptive crossover and mutation formulae that can provide appropriate crossover operator and mutation operator based on different functions of the objects and the number of iterations. The performance of ISMC was tested by the benchmark functions. The simulation results for residue hydrogenating kinetics model parameter estimation show that the proposed method is superior to the traditional intelligent algorithms in terms of convergence accuracy and stability in solving the complex parameter optimization problems. 展开更多
关键词 optimization algorithm membrane computing benchmark function improved self-adaptive operator
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Hybrid Improved Self-adaptive Differential Evolution and Nelder-Mead Simplex Method for Solving Constrained Real-Parameters
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作者 Ngoc-Tam Bui Hieu Pham Hiroshi Hasegawa 《Journal of Mechanics Engineering and Automation》 2013年第9期551-559,共9页
In this paper, a new hybrid algorithm based on exploration power of a new improvement self-adaptive strategy for controlling parameters in DE (differential evolution) algorithm and exploitation capability of Nelder-... In this paper, a new hybrid algorithm based on exploration power of a new improvement self-adaptive strategy for controlling parameters in DE (differential evolution) algorithm and exploitation capability of Nelder-Mead simplex method is presented (HISADE-NMS). The DE has been used in many practical cases and has demonstrated good convergence properties. It has only a few control parameters as number of particles (NP), scaling factor (F) and crossover control (CR), which are kept fixed throughout the entire evolutionary process. However, these control parameters are very sensitive to the setting of the control parameters based on their experiments. The value of control parameters depends on the characteristics of each objective function, therefore, we have to tune their value in each problem that mean it will take too long time to perform. In the new manner, we present a new version of the DE algorithm for obtaining self-adaptive control parameter settings. Some modifications are imposed on DE to improve its capability and efficiency while being hybridized with Nelder-Mead simplex method. To valid the robustness of new hybrid algorithm, we apply it to solve some examples of structural optimization constraints. 展开更多
关键词 Differential evolution hybrid algorithms evolutionary computation global search local search simplex method.
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Modified Self-adaptive Immune Genetic Algorithm for Optimization of Combustion Side Reaction of p-Xylene Oxidation 被引量:1
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作者 陶莉莉 孔祥东 +1 位作者 钟伟民 钱锋 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2012年第6期1047-1052,共6页
In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation fa... In recent years, immune genetic algorithm (IGA) is gaining popularity for finding the optimal solution for non-linear optimization problems in many engineering applications. However, IGA with deterministic mutation factor suffers from the problem of premature convergence. In this study, a modified self-adaptive immune genetic algorithm (MSIGA) with two memory bases, in which immune concepts are applied to determine the mutation parameters, is proposed to improve the searching ability of the algorithm and maintain population diversity. Performance comparisons with other well-known population-based iterative algorithms show that the proposed method converges quickly to the global optimum and overcomes premature problem. This algorithm is applied to optimize a feed forward neural network to measure the content of products in the combustion side reaction of p-xylene oxidation, and satisfactory results are obtained. 展开更多
关键词 self-adaptive immune genetic algorithm artificial neural network measurement p-xylene oxidation process
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Synthesis and optimization of utility system using parameter adaptive differential evolution algorithm
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作者 李泽秋 杜文莉 +1 位作者 赵亮 钱锋 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2015年第8期1350-1356,共7页
Synthesis and optimization of utility system usually involve grassroots design, retrofitting and operation optimization, which should be considered in modeling process. This paper presents a general method for synthes... Synthesis and optimization of utility system usually involve grassroots design, retrofitting and operation optimization, which should be considered in modeling process. This paper presents a general method for synthesis and optimization of a utility system. In this method, superstructure based mathematical model is established, in which different modeling methods are chosen based on the application. A binary code based parameter adaptive differential evolution algorithm is used to obtain the optimal con figuration and operation conditions of the system. The evolution algorithm and models are interactively used in the calculation, which ensures the feasibility of con figuration and improves computational ef ficiency. The capability and effectiveness of the proposed approach are demonstrated by three typical case studies. 展开更多
关键词 Utility system synthesis MINLP Operation optimization
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Research on Network-on-chip Dynamic and Adaptive Algorithm and Choice Strategy
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作者 Dong Li 《International Journal of Technology Management》 2013年第2期15-19,共5页
With further increase of the number of on-chip device, the bus structure has not met the requirements. In order to make better communication between each part, the chip designers need to explore a new structure to sol... With further increase of the number of on-chip device, the bus structure has not met the requirements. In order to make better communication between each part, the chip designers need to explore a new structure to solve the interconnection of on-chip device. The paper proposes a network-on-chip dynamic and adaptive algorithm which selects NoC platform with 2-dimension mesh as the carrier, incorporates communication energy consumption and delay into unified cost function and uses ant colony optimization to realize NOC map facing energy consumption and delay. The experiment indicates that compared with random map, single objective optimization can separately saves (30% - 47 %) and ( 20% - 39%) in communication energy consumption and execution time compared with random map, and joint objective optimization can further excavate the potential of time dimension in mapping scheme dominated by the energy. 展开更多
关键词 NETWORK-ON-CHIP system on chip energy consumption DELAY MAP
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Numerical Homogenization of the Elliptic Problem with Rapidly Varying Tensor or Boundary Condition
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作者 Jack Urombo Ephraim Makoni 《Journal of Mathematics and System Science》 2014年第6期421-432,共12页
Homogenization is concerned with obtaining the average properties of a material. The problem on its own has no easy solution, except in cases like the periodic case, when it can be obtained in closed form. In this pap... Homogenization is concerned with obtaining the average properties of a material. The problem on its own has no easy solution, except in cases like the periodic case, when it can be obtained in closed form. In this paper we consider a numerical solution of the elliptic homogenization problem for the case of rapidly varying tensor or boundary conditions. The method makes use of an adaptive finite element method to correctly capture the rapid change in the tensor or boundary condition. In the numerical experiments we vary the mesh size and do a posteriori error analysis on test problems. 展开更多
关键词 2. Homogenization Elliptic equation
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