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Allocating appropriate channels to the users (UE) is an important challenge in mobile networks. Heuristics Algorithm may be used to solve this problem. In this paper, a new time slot allocation (TSA) algorithm based on genetic algorithm (GA) is proposed after comparing to the dynamic queue TSA algorithm. The new algorithm is simulated and analyzed on the TD-SCDMA Radio Resource Management Simulation...
Gear reducer is one of the most widely used methods in mechanical transmission, optimization of which is of great significance in improving the bearing capacity, prolonging service life and reducing its size and quality. By Visual Basic programming mixed with MATLAB, automatic optimization design for gear reducer is realized in the paper, design efficiency and quality greatly improved. Genetic algorithm...
With the development of network, users'services put forward diverse demands on the network QoS (Quality of Service), the QoS routing is the optimization problem under the satisfaction of multiple QoS constraints. This paper firstly sets up a multi-constrained QoS routing model and constructs the fitness value function by transforming the QoS constraints with a penalty function. Secondly, we merge...
Direct marketing forecasting models have focused on estimating the response probabilities of consumer purchases and neglected the profitability of customers. This study proposes a method of constrained optimization using genetic algorithm to maximize the profitability at the top deciles of a customer list. We apply this method to a direct marketing dataset using tenfold cross validation. The results...
In this paper, we proposed an improved niche genetic algorithm on the basis of the density clustering-based DBSCAN algorithm which can distinct between niches dynamically and maintain the ability of population diversity. Its application in the field of closed-cell material optimization shows that the algorithm can effectively overcome some shortcomings, such as prematurity, poor local search capabilities...
The ARMA model is the most basic sequential method and the practical application of the most comprehensive time series model. It expands and develops in the linear regression model foundation. The ARMA model not only may promulgate dynamic data's structure and the rule, will forecast its future value, moreover may also from the various research system's related characteristic, the ARMA model's parameter...
In this paper, we propose a correlation method to assess image quality based on support vector machine (SVM) and genetic algorithm (GA). Instead of the simple linear function to correlate objective indicators with subjective scores of images, we introduce SVM for the correlation function, make GA as the search algorithm, and finally get the image quality assessment model. The results of experiments...
Before performing the DNA computation, a set of specific DNA sequences are required. However, this is a burdensome task as too many constraints need to be satisfied. In this paper, ant colony algorithm is applied to solve the problem of DNA codewords design. Inspired by the traveling salesman problem, first a city matrix with T rows and S columns is designed, in which every city denotes a DNA sequence...
To resolve the difficulty in processing fringe image with heavy noise and low contrast in non-contact measurement based on conoscopic holography, B-splines function is calculated to approximate the phase from a single closed fringe pattern by conoscopic holography, which is fitted over the sub-image obtained from every space interval in a scanning window. Instead of fringe frequency used before, unwrap...
A reactive power optimization is a multi-modal, mixed-variable, multi-constraint and nonlinear planning problem. In the last decades, many computational intelligence-based techniques have been proposed for reactive power optimization problem, such as genetic algorithm (GA), particle swarm optimization (PSO), differential evolution (DE), Tabu search. Recently, a new swarm intelligent algorithm, social...
Fly ash unburned carbon content is an important factor affect the boiler thermal's efficiency. Least squares support vector machine is more suitable for real-boiler test conditions with fewer small sample study,We introduced this method into power plant boiler fly ash carbon content prediction model, established complex models relationship between the boiler fly ash carbon content characteristics...
The technology of information filtering may help the people to pick out the interested information and shield the unnecessary information. Facing the new challenge of the real-time online network information filtration, the technology of the adaptive information filtering appears to be very important in this case. In aspects of the self-learning of user template for adaptive information filtering,...
A new adaptive mutation method, which uses the information of relative importance of chromosomes and alleles, is proposed for genetic algorithm(GA). In each generation, suitable chromosomes for mutation are automatically choosed based on cumulative distribution function of chromosomes fitness, without requiring to set the mutation probability anymore. After selecting chromosomes for mutation, the...
In the multi-objective transportation (MOT) optimization problems, it is quite necessary to consider the tradeoff between all conflictive sub-objectives, consequently it leads to difficulties in solving. So this paper proposed a new Fuzzy Multi-Population Cooperative Genetic Algorithm, called fmc-GA. We firstly infuse the combination of fuzzy rule, which is convenient to express the explicit knowledge,...
In this paper, a 4PL Routing Problem (4PLRP) with fuzzy duration time is presented where the fuzzy numbers is used to describe the uncertainty of the duration time. After the description of 4PLRP, a fuzzy programming model is established according to the uncertainty theory. And a crisp equivalent is derived when fuzzy variables are characterized by triangular fuzzy numbers. Then a Kth shortest path...
Taking the shortest distance as the performance index and the 6-DOF fruit picking robot as the research object, the various points of path that robot passed are planned with the genetic algorithm, considering the joint velocity, acceleration and acceleration restriction. The results which are simulated with robotics toolbox of matlab indicate that the method of robot path planning not only ensures...
Genetic algorithm was introduced into the particle filtering in this paper. With the ability of global searching and optimizing, genetic algorithm overcomes the phenomenon of degeneracy and sample impoverishment. By simulation, the results show that the use of genetic algorithm to particle filtering is feasible, and this method is superior to the traditional re-sampling algorithm. Finally, the virtual...
Real-coded genetic algorithms (RCGAs) have been effectively used to solve constrained optimization problems (COPs). However, the crossover operators do not have mechanisms to handle constraints and there is no guarantee that if the parents satisfy some constraints the offspring will satisfy them as well. Degree preserving based crossover operators are proposed to increase the probability of constructing...
The fuzzy rules-based weighted sum Genetic Algorithm (Fuzzy-WSGA) is proposed in the paper to solve the multi-objective fixed-charged transportation optimization problem (mfcTP). We put forward the elite preserving strategy when the Pareto optimal solutions are built by the arena's principle, which used weighted sum based on the AP algorithm to evaluate the fitness function and preserve the elite...
A new genetic algorithm, combined cultivating with migrating operators (CMGA), is proposed. Cultivating operator can make gene segments of chromosomes keep superior characteristics at a higher probability. A new migrating schema with directed direction guided by illumination information is discussed, and it can overcome the blindness and invalidity in genetic operations. We focus on key factors of...
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