Spread Spectrum Code Estimation by Artificial Fish Swarm Algorithm

Efficient Job Scheduling in Grid Computing with Modified Artificial Fish Swarm Algorithm

“…With the aid of the object-oriented analytical method, we can regard the artificial fish as an entity encapsulated with one's own data and a series of behaviors, which can accept amazing information of environment by sense organs, and do stimulant reaction by the control of tail and fin. solutions at present and the states of other companions), and it influences the environment via its own activities and other companions' activities [29]. The AF realizes external perception by its vision shown in Fig.1.…”

“…The greater number of inspecting tour the AF does, the more knowledge about overall states of the vision the AF obtains. Certainly, it does not need to travel throughout complex or infinite states, which is helpful to find the global optimum by allowing certain local optimum with some uncertainty [29]. Let X=(x1, x2, …, xn) and Xv=(x1v, x2v, …xnv), then process can be expressed as follows:…”

“…They have some common characters and also have their unique characters. AFSA as a new optimization algorithm becomes a very hot topic, it offers new ideas to solve the optimization problem in signal processing [16], complex function optimization [17], neural network classifiers [18], network combinatorial optimization [19], multi-user detection in communication [20][21], sequence code estimation [22], and some applications [23].…”

“…ARTIFICIAL FISH SWARM ALGORITHM The basic idea of AFSA is to imitate the fish behaviors such as preying, swarming, following with local search of fish individual for reaching the global optimum; it is random and parallel search algorithm. The AFSA is generated from long observation of fish swarm in nature, using the swarm intelligence in the solution of the optimization problem, and combining with the artificial intelligence [29].…”

A New Approach to Weapon-Target Assignment in Cooperative Air Combat

“…The artificial fish swarm algorithm (AFSA) simulating the behavior of a fish inside water was proposed by Li et al [18] and has already been applied in engineering contexts [19][20][21][22][23][24]. The main artificial fish behaviors are random, chasing, swarming, and searching, which allows the algorithm to act better in global searching but poor in local searching.…”