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To improve protein folding simulations, a novel chaotic clonal genetic algorithm (CCGA) was investigated on a 2D lattice model. The novel algorithm combines chaos operator, clonal selection algorithm, and genetic algorithm. We compared CCGA with standard genetic algorithm (SGA) and immune genetic algorithm (IGA) for various chain lengths. It has shown that CCGA not only find global minima more reliably,...
Considering the weight coefficients problem in multi objective evaluation of optimum FRP fishing vessel type, this paper proposed an interactive satisfactory method for Genetic Algorithm (GA). Differing from the traditional Economic and technological evaluation, the paper doesn't firstly select several feasible projects to sort them by fuzzy comprehensive evaluation or linear weighted evaluation,...
Aiming at the robot problems such as little relevance, low accuracy of the simultaneous localization and map building (SLAM) and easy locking, lack of initiative of the navigation system, the multi-sensor vision system is introduced, and then unifying the data of each sensor by world coordinate system of global calibration based on the local calibration of each vision sensor module, a serial of local...
Design of prestressed concrete aqueduct is involved in multidimensional variables non-linear optimal problem, although there are many traditional optimization methods. However, more or less disadvantages of these traditional methods affect optimization results. As a result, a new method of Improved Genetic Algorithm which have better search capability and global optimization is applied in Xinjiang...
An approach based on genetic simulated annealing algorithm is proposed, which is used to solve bandwidth, delay, delay variation constraints minimum- cost multicast routing problem. In the algorithm, aiming at the limitation of genetic algorithm, integral sequence encoding method based on the preparative routes set is adopted, and the fitness function is adjusted. The cross-over and mutation method...
In view of the complexity of Back Analysis of rock-fill material parameter, this paper uses genetic algorithm optimization BP neural network weights and threshold, simulated finite element calculation of rockfill dam by genetic neural network, combined with the theory of particle swarm optimization algorithm, and has realized inverse analysis of particle swarm optimization and genetic neural network...
Power consumption has become one of most serious challenges for SoC design. Among the various methods, Multiple Supply Voltage (MSV) is an effective method for power reduction. In this paper, Genetic Algorithm (GA) is used to optimize the Voltage Islands-Aware Multiple Voltage Assignment (VIAMVA). A cost function is developed to take the overhead of level shifters and the complexity of power network...
This article is based on the theoretical study and experimental analysis of multi-objective genetic algorithm and artificial immune algorithm's characteristics, and presents a method which is based on immune genetic algorithm to solve multi-objective optimization problems. The main contents are as follows: Firstly, the multi-objective optimization problems are described. Secondly, this paper designs...
The transmission tower shape can be optimized by genetic algorithm to acquire the maximum fundamental frequency, Considering that there are some disadvantages such as premature convergence and low robustness in solving complex optimization problems with standard genetic algorithm, a new adaptive strategy is proposed to improve the performance of the algorithm, including the design for selection mechanism...
With the informationization of mechanical devices, high precision sensors have been widely applied to all kinds of mechanical devices for the information gathering. However, as the sensors are produced by various research centers and manufacturers, there is a considerable difficulty in examining and identifying the sensors. In this article, A new intelligent analysis model based on BP+GA algorithms...
A complete supply chain, from a cycle point of view taking into account the integrity of the logistics cycle, should include the forward and reverse logistics. Therefore, taking into account both original forward logistics system and the reverse logistics, in this paper the one-way logistics will be transformed into two-way logistics under the premise of the most savings capital, and the logistics...
Logistics distribution region partition problem is a nondeterministic polynomial problem. It is significant to solve distribution region partition of multi-distribution centers and multi-transfer stations. Logistics distribution region is divided up into different distribution units by cluster methods, multi-distribution centers and multi-transfer stations under the mathematical models of regional...
The location problem is one kind of special type optimized problems. The Min-max weighted distance problem is a new class of location problem, its decision problem is a NP-Complete problem. This paper designs a genetic algorithm by some properties of the problem, and gives the design and selection method of crossover operator, mutation operator and reproduction operator.
The K-means algorithm is widely used because of its reliable theory, simple algorithm, fast convergence and it can effectively handle large data sets. However, the traditional K-means algorithm is sensitive to the initial cluster centers; make the average of all objects in the same class as cluster centers, so clustering results is largely affected by the isolated points. To address the problems,...
An improved quantum genetic algorithm (IQGA) is proposed for path planning of mobile robot in unknown environment, which uses problem-specific quantum genetic algorithm for robot path planning instead of the standard genetic algorithm(GA) and quantum genetic algorithm(QGA). Six genetic operators operated chromosomes and improved fitness function to evaluate new individuals, and this algorithm is capable...
The existing particle swarm optimization (PSO) and genetic algorithms (GA) could not solve some discrete-valued problems effectively such as Endmember extraction in hyperspectral imagery. Firstly, the theory of particle swarm optimization was reviewed, and a genetic algorithm based Endmember extraction method was analyzed, which combined with the convex geometry theory. Then, a particle swarm optimization...
To solve the traditional fault diagnosis can not be adapted to the complicated system, a kind of new multi-sensor fusion fault diagnosis method is presented. The method applies the theory of genetic algorithms and fuzzy logic to the BP (back propagation) neural network. Combined with BP and GA, it walks in several steps. Firstly, the best individual is chosen in current population and trained in order...
This paper presents an improved adaptive genetic algorithm for integration optimization design of active vibration isolation system. During the operation of the algorithm, according to the individual fitness, the crossover rate and mutation rate make adaptive adjustments in accordance with the sigmoid function curve, and individuals of each generation are saved according to optimal preservation strategy...
In this paper, an improved genetic algorithm to solve the unicast routing problem with QoS restrictions is proposed. The proposed algorithm uses real-coded strategy, which has unique crossover strategy, mutation strategy and fitness function, and in addition, the strategy of introducing alien species is adopted in the algorithm, in order to enhance the algorithm's global search ability. The simulation...
In this paper, a multi-objective evolutionary algorithm, the non-dominated sorting genetic algorithm (NSGA-II), is applied to examine the operations of four cascade reservoirs system in the upper Wujiang River, Guizhou Province of China. The Optimization model is established with two objects, which are the maximal generation of and the firm power in certain probability. The NSGA-II is applied to simulate...
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