To solve the difficulty in selecting crossover probability and mutation genetic algorithms, a fuzzy immune algorithm based on adaptive estimation of reasoning system is proposed, it used parameter optimization design two-degree-of-freedom PID controller. According to experiment simulation results, classic evolution tends halt after 37 generations, with fitness value 7.135, whereas stop 20 7.486...

The biological observation of the difference in the mutation rates of allele on different loci is implemented in genetic algorithm so that the mutation rate is both time and locus dependent. The performance of this new locus oriented adaptive genetic algorithm (LOAGA) is evaluated on the test problem of zero/one knapsack for various sizes. It is found that LOAGA can solve the single constraint ...

Differential evolution is one of the most prestigious population-based stochastic optimization algorithm for black-box problems. The performance a differential depends highly on its mutation and crossover strategy associated control parameters. However, determination process suitable parameter setting troublesome time consuming. Adaptive methods that can adapt to problem landscape environment a...

Recent theoretical research has shown that self-adjusting and self-adaptive mechanisms can provably outperform static settings in evolutionary algorithms for binary search spaces. However, the vast majority of these studies focuses on unimodal functions which do not require algorithm to flip several bits simultaneously make progress. In fact, existing are designed detect local optima have any o...

In order to improve the prediction accuracy of ionospheric total electron content (TEC), a combined intelligent model (MMAdapGA-BP-NN) based on multi-mutation, multi-cross adaptive genetic algorithm (MMAdapGA) and back propagation neural network (BP-NN) was proposed. The combines international reference ionosphere (IRI), statistical machine learning (SML), BP-NN, MMAdapGA. Compared with IRI, SM...

We present a new tierra-inspired artiicial life system with local interactions and two-dimensional geometry , based on an update mechanism akin to that of 2D cellular automata. We nd that the spatial geometry is conducive to the development of diversity and thus improves adaptive capabilities. We also demonstrate the adaptive strength of the system by breeding cells with simple computational ab...

An evolutionary method is proposed for the constrained optimization of chemical engineering processes. Apart from the classical mutation, crossover and creep (small mutation), it makes use of several novel reproductive operators: shift, smoothing, extrapolation and swapping. An adaptive mutation rate is used to guard against stalling at local peaks. The method was able to solve dynamic optimiza...

In this paper, we propose a radically new paradigm of the Adaptive Networking Architecture for Service Emergence (ANA-SE). In the proposed architecture, services are implemented by a collection of multiple entities called cyber-entities. These cyber-entities have functionality related to their service and follow simple behavior rules (e.g., migration, reproduction, energy exchange, mutation, de...

The choice of mutation rate is a vital factor in the success of any genetic algorithm (GA), and for permutation representations this is compounded by the availability of several alternative mutation operators. It is now well understood that there is no one “optimal choice” rather the situation changes per problem instance and during evolution. This paper examines whether this choice can be left...

Aiming at solving the problems of large calculation, time-consuming, and low segmentation accuracy multi-threshold image segmentation, an adaptive threshold value based differential evolution algorithm is proposed in this paper. Firstly, opposite learning strategy introduced into initial population to improve quality population; secondly, a threshold-value-based mutation balance exploration dev...