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Permeability coefficients of dam foundation are inversed on the base of real water heads. Otherwise, simple genetic algorithm has the disadvantages in determining the optimal probability values of the crossover and mutation, computation quantity is great and premature phenomena easily appears. Adaptive genetic algorithm is proposed to overcome the disadvantages which simple genetic algorithm has....
In the present water-supply monitoring system, every pipe network monitoring point is distributed in the range wide, in large quantity, in long distance, and not centralized, so there is certain difficulty to control. Through bringing in the theory of Multi-Agent, this text has proposed a kind of new-type long-range monitoring system of water-supply based on multi-agent. The system consists of control...
This paper proposes a new evolution algorithm, M_GEP, based on the concept of multi-gene chromosome in gene expression programming. The algorithm has two characters: (1) a chromosome is composed of more than one gene; (2) the sub-genes are linked together according to the linking gene which may conclude more than one kind of function. We give two examples, whose results show that the models set up...
In this paper we investigate the global optimization problems with bounded variables and linear equality constraints. We suggest an approach to drawing sample points randomly from the feasible region. A new population-based global optimization algorithm is proposed. We also show that the algorithm converges to the global optimal solution with probability one. The method is easily extended to global...
Adaptive inertia weight is proposed to rationally balance the global exploration and local exploitation abilities for particle swarm optimization. This paper describes an adaptive strategy for tuning the inertia weight parameter of the PSO algorithm - Exponential type adaptive inertia weighted Particle Swarm Optimization (EPSO). This adaptive tuning strategy is based on the inertia weight dynamic...
Based on the perfect rationality and common knowledge theoretically hypotheses, the out-of-equilibrium outcome or out of subgame perfect equilibrium path couldn't achieve in traditional game theory. Evolutionary game theory analyzes the population's dispersive behaviors under the bounded rational hypothesis. The theoretical payoffs of different strategies are decided by the practical observed outcome,...
Genetic operators play an important role in Evolution Strategies (ES). There are two important issues in the evolution process of the genetic search: exploration and exploitation. We analyze the impact of the genetic operators in ES. The Classical Evolution Strategies (CES) relies on Gaussian mutation, whereas Fast Evolution Strategies (FES) selects Cauchy distribution as the primary mutation operator...
The famous Todaro model could not explain the circulative flowed phenomenon in the course of rural labor transfer. The paper uses Sethi's generic replicator dynamic model (1998) of evolutionary game theory to explain the circulative flowed phenomenon based Chinese statistical data. It builds the urban-rural ternary-structure model including rural section, urban informal section and urban formal section,...
Multi-objective optimization problems (MOPs) in real world are often constrained optimization problems. So test problems to evaluate multi-objective optimization evolutionary algorithms (MOEAs) should have some constraints in order to simulate real-world problems. In this paper, a well understood and tunable constrained test problems generator is suggested. By setting parameters in the constraint...
There are many complex industrial processes with highly nonlinear and uncertain characteristics which are generally difficult to control by well known PID controllers. Active disturbance rejection control (ADRC), a relatively recent nonlinear control method, is an alternative framework which has the advantages on simple algorithm, strong robustness, and less dependence on the mathematical models of...
Multi-finger microaccelerometer are microelectromechanical systems (MEMS) devices based on IC technology and micro-machining technology, which are widely implemented both in military and civilian fields. Robust Collaborative Optimization (RCO) method is built based on CO method. The research establishes the RCO Model based on genetic algorithm for the problem, and proposes a MATLAB program to calculate...
On the basis of the analysis of canonical genetic algorithm's shortage, a novel genetic algorithm based on dynastic changes mechanism of nation (DCGA) is proposed. In DCGA, populations one by one evolve according to the relay race mode, by which the DCGA holds a mechanism of transferring from a local optimal solution to another better one and finally finding the global optimal solution under the guidance...
Classification is an important problem in data mining. This paper focuses on a method of optimizing classifiers of neural network by Genetic Algorithm based on principle of gene reconfiguration, and implement classification by training the weight. The paper uses shift reverse logic crossover operation and the improved genetic algorithm The article using the typical method for optimizing BP neural...
Forecasting method using neural networks has been advocated as an alternative to traditional statistical forecasting in recent years. The paper built a feed-forward neural network model to forecast the values of governmentpsilas financial educational fund (GFEF) in year 2010. On the basis of data processing, the structure of neural networks was given. The algorithm that adopted as a learning phase...
Although the decision support systems (DSS) theory and application has already taken significant progress, the development of DSS is strongly challenged for the bottleneck of existing serial characters store and process mechanism. The neural network is an ultra large-scale, time dynamic system with highly nonlinear. Its most important features are paralleled distributive treatment with large scale,...
By integrating the global searching advantage of Genetic Algorithm (GA) and the local searching ability of BP Artificial Neural Network (BP ANN), this paper proposes a new model of BP ANN based on GA (called GA-BP ANN). Firstly, it applies GA to optimize the initial interconnecting weights and thresholds of BP ANN. Then, it utilizes the BP algorithm to train the neural network more accurately. This...
A prediction model of compression ratio for extruded oilseeds was developed based on improved BP neural networks. As an applied example, the predicted curves were successfully used to predict critical pressing pressures. Results indicated that the predicted values of compression ratios conformed to the measured values well for extruded cottonseed and castor been. There was a limiting compression for...
The particle swarm optimization was applied in BP neural network training. It reasonably confirms threshold and connection weight of neural network, and improves capability of solving problems in realities. Meanwhile, PSO-BP neural network is applied into classification of fabric defect. The method of orthogonal wavelet transform was used to decompose monolayer from fabric image. And the sub-images...
Neural network is a type of network that carries out information processing through the interaction of neurons. The storage of knowledge and information shows distributed physical connection of mutual-linking network components. Bi-directional associative memories (BAM) neural network is a type of feedback neural network system of bi-directional stability, which exists simple characteristics that...
The pollution of Qinhuangdao Port is the bottleneck of economic development, so how to correct the environmental assessment of the work environment has important significance. The main pollutants in Qinhuangdao port is coal dust pollution, through various observation points on the measurement indicators of pollutants by EPA experts scoring can get a group of data, and then through various BP neural...
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