TSP has been studied in many methods by various algorithms, with the increase of the TSP scale, there are some problems appear in the related solution,such as solving the optimal solution and so on. With the increasin...
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ISBN:
(纸本)9783037852828
TSP has been studied in many methods by various algorithms, with the increase of the TSP scale, there are some problems appear in the related solution,such as solving the optimal solution and so on. With the increasing calculation nodes, the convergence degree and computing difficulty of TSP will increase enormously. artificialfish is an optimize algorithm based on biology model putting forward at present. Proposed a solution for TSP based on the artificial fish algorithm, describes the mathematic model of TSP, and Expounds the steps of the algorithm in details, by testing the algorithm, we know that, the algorithm can obtain the best solution, in global search, convergence rate but the robustness has to be improved in the future.
TSP is well-known issue in the field of mathematics. With the increasing calculation nodes, the convergence degree and computing difficulty of TSP will increase enormously. artificialfish is an optimize algorithm bas...
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ISBN:
(纸本)9780769536453
TSP is well-known issue in the field of mathematics. With the increasing calculation nodes, the convergence degree and computing difficulty of TSP will increase enormously. artificialfish is an optimize algorithm based on biology model putting forward at present. We describe the relative knowledge of artificial fish algorithm, propose an artificial fish algorithm model for TSP, then make the qualitative analysis of the basic process for simulating TSP.
Ensemble learning has become a hot topic in the machine learning recently. The generalization performance of ensemble classification systems has been improved dramatically by training and combining some accurate and d...
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ISBN:
(纸本)9783642340406
Ensemble learning has become a hot topic in the machine learning recently. The generalization performance of ensemble classification systems has been improved dramatically by training and combining some accurate and diverse *** model of support vector machine(SVM) ensemble based on artificialfish_swarm algorithm(AFSA) is proposed after analyzing the drawbacks of the known algorithms such as GASEN and CLU_ENN. The AFSA is used to optimize the ensemble weights of base SVMs for SVM ensemble after individual SVM of ensemble is trained. Those SVMs with weights larger than a given threshold value are ensembled. The method of selective ensemble is achieved to obtain better performance than traditional ones that ensemble all of the base SVMs. The simulated experiment results on UCI and StatLog show that the proposed method has better performance and the AFSA has its superiority on optimizing weights of SVM ensembles, and also on operation efficiency.
In the paper, we proposed big data novel filtering method – Local-loop Particle Filter Based on the artificial fish algorithm(LPF-AF) for nonlinear dynamic systems. Particle filtering algorithm has been widely used i...
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ISBN:
(纸本)9781510870604
In the paper, we proposed big data novel filtering method – Local-loop Particle Filter Based on the artificial fish algorithm(LPF-AF) for nonlinear dynamic systems. Particle filtering algorithm has been widely used in solving nonlinear/non Gaussian filtering problems. The proposal distribution is the key issue of the particle filtering, which will greatly influence the performance of algorithm. In the proposed LPF-AF, the local searching of AF is used to regenerate sample particles, which can make the proposal distribution more closed to the poster distribution. There are mainly two steps in the proposed filter. In the first step of LPF-AF, extended kalman filter was used as proposal distribution to generate particles, then means and variances of the proposal distribution can be calculated. In the second step, some particles move to toward the particle with the biggest weights. The proposed LPF-AF algorithm was compared with other several filtering algorithms and the experimental results show that means and variances of LPF-AF are lower than other filtering algorithms.
Due to the scarcity of fresh water resources, exploiting dams' reservoirs, based on their optimal operation, obviates construction of extra dams and high costs and satisfies downstream consumers' water needs w...
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Due to the scarcity of fresh water resources, exploiting dams' reservoirs, based on their optimal operation, obviates construction of extra dams and high costs and satisfies downstream consumers' water needs with high reliability. In this research, a new hybrid approach of artificialfish Swarm algorithm (AFSA) and Particle Swarm Optimization algorithm (PSOA) is used to optimize Karun-4 reservoir, increase energy production and minimize downstream water shortages. This Hybrid algorithm (HA) brings about diversity of responses in PSOA, prevents entrapment of AFSA in local optimum traps and increases convergence speed and balances between the abilities to scan and make profit in the AFSA. This method was assessed based on reliability, vulnerability and resilience indices. In addition, based on a multi-criteria decision-making model, it was evaluated by comparing it with other evolutionary algorithms. To verify the HA, it was tested on few mathematical functions. Results indicated that the HA features performed higher reliability, lower vulnerability and resiliency, as compared with AFSA and PSOA. In addition, HA is ranked first according to the multi criteria decision making model. Further, among all the tested evolutionary methods, this new algorithm yielded the best answer for dam power plant's objective function.
An optimization of multi-varieties and small-batch of production scheduling is proposed, which is embodied the utilization ratio of equipment. First, the production scheduling model with multi-varieties and small-batc...
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ISBN:
(纸本)9783037855744
An optimization of multi-varieties and small-batch of production scheduling is proposed, which is embodied the utilization ratio of equipment. First, the production scheduling model with multi-varieties and small-batch is improved by adding a new constraint. Second, the feeding behavior, clustering and rear collision of artificial fish algorithm are improved in order to describe the multi-varieties and small-batch of production scheduling. Finally, the optimizing results influenced by iteration times and quantity of artificialfish are analyzed. The experiments show that the utilization ratio of equipments are nearly same and the Man Hour is decreased obviously while the optimization method is used, which testifies the validity of the new optimization method.
This paper analyzes the characteristics of MMAS and artificial fish algorithm;find their similarity optimization mechanism,combining with the advantages of two methods,and this paper puts forward a new hybrid bionic o...
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This paper analyzes the characteristics of MMAS and artificial fish algorithm;find their similarity optimization mechanism,combining with the advantages of two methods,and this paper puts forward a new hybrid bionic optimization algorithm;it can improve the efficiency of optimization *** to choose the most appropriate parameters or mainly based on low parameter requirements algorithm to combination of more efficient intelligent algorithm is the research work we want to continue,and design some more efficient adaptive algorithm to solving practical problems.
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