In the seismic inversion model, as the neural network algorithm there are some problems, the convergence bad, accuracy is not high. This paper presents a seismic inversion based on artificial fish Swarm Optimization neural network models. First to initialize fish mapping of chaos optimization and ergodicity of artificial fish-swarm search and adaptive strategies of artificial fish-swarm algorit...

In This study, a new artificial fish-swarm optimization, to improve the foraging behavior of artificial fish swarm algorithm is closer to reality in order to let the fish foraging behavior, increase a look at the link (search) ambient, after examining environment, artificial fish can get more status information of the surrounding environment. Artificial fish screened from the information obtain...

An improved quantum artificial fish swarm algorithm is proposed in this paper. Based on that quantum computing have exponential acceleration for heuristic algorithm, by examining eight most recent patents and some literatures in the area of artificial fish swarm algorithm and quantum computing. The new algorithm uses qubits to code artificial fish and quantum revolving gate, preying behavior, f...

In view of the bad convergence performance and low precision of standard artificial fish swarm algorithm in the water quality properties identification, this paper put forward an improved identification model based on adaptive parameters optimization. Firstly, it optimized the immune cloning and selection algorithm (ICSA) in periodic mutation operator and selection operator. Then it introduced ...

An improved quantum artificial fish swarm algorithm (IQAFSA) for solving distributed network programming considering distributed generation is proposed in this work. The IQAFSA based on quantum computing which has exponential acceleration for heuristic algorithm uses quantum bits to code artificial fish and quantum revolving gate, preying behavior, and following behavior and variation of quantu...

This article introduces two swarm intelligent algorithms, a group search optimizer (GSO) and an artificial fish swarm algorithm (AFSA). A single intelligent algorithm always has both merits in its specific formulation and deficiencies due to its inherent limitations. Therefore, we propose a mixture of these algorithms to create a new hybrid optimization algorithm known as the group search-artif...

With regard to the subject of sensor network node optimization, a strategy for wireless sensor network coverage optimization based on improved fish swarm algorithm is proposed in this paper. The improved algorithm is targeted on network coverage, node utilization rate and energy consumption balance, which makes use of the ergodic property of chaotic motion to overcome the disadvantage that arti...

The paper focuses on a capacitated vehicle routing problem with two objectives: one is attainment of specific load factor and the other is minimization of total travel cost. Our approach is based on artificial fish swarm algorithm, a swarm-based heuristic, which mimics the foraging behaviour of a fish swarm. After initializing a school of artificial fish, whose validity is guaranteed by a desig...

K-medoids clustering algorithm is used to classify data, but the approach is sensitive to the initial selection of the centers and the divided cluster quality is not high. Basic Artificial Fish Swarm Algorithm is a new type of heuristic swarm intelligence algorithm, but optimization is difficult to get a very high precision due to the randomness of the artificial fish behavior. A novel clusteri...