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This essay proposes a maximum variance between clusters method of image segmentation (OTSU) based on PSO. The method in this paper makes use of particle swarm algorithm and achieves a great acceleration to the traditional OTSU. On that basis, we also applied the parallelism technology in particle-swarm algorithm and find an optimal threshold, so we can segment images with this threshold. The result...
In this paper, we point out that conventional differential evolution (CDE) algorithm runs the risk of being trapped by local optima because of its greedy updating strategy and intrinsic differential property. A novel simulated annealing differential evolution (SADE) algorithm is proposed to improve the premature property of CDE. With the aid of simulated annealing updating strategy, SADE is able to...
Fuzzy extension matrix (FEM) inductive learning is an important method that generates knowledge from cases. Compared with conventional extension matrix techniques, it is more powerful and practical to handle with ambiguities in classification problems. Rule extraction from fuzzy extension matrix involves three parameters alpha, beta and gamma. These parameters play an importation role in the entire...
In order to detect the corrosion of grounding grids, a corrosion diagnosis approach based on Tabu search (TS) algorithm is put forward. A grounding grid is excited between couples of touchable nodes by a current source. Some voltages of touchable nodes are measured in each excitation. Minimizing the energy of the error between testing voltages and evaluation voltages is used as the index. The designed...
Frequent itemsets are crucial to many tasks in data mining. A new algorithm for finding all frequent itemsets is proposed in this paper. In data mining, the process of counting any itemset's support requires a great I/O and computing cost. An impacted bitmap technique to speed up the counting process is employed in this paper. Nevertheless, saving the intact bitmap usually has a big space requirement...
Genetic algorithm offers the common frame of resolving optimization problem by imitating biological evolution based on natural selection. However it has some drawbacks such as slow convergence and being premature. In genetic algorithm, individual generated by genetic operation is a bit random and even sometimes more inferior than its parents. So a new operator - negative selection that can filtrate...
To solve the problem of network expansion, an improved particle swarm optimization algorithm (PSO) is proposed in this paper. This method initialized the particle swarm according to borderline search mind, made the initialized particle near the safety line, overcomes the defect of the uncertainty in the rational distribution of particle initialization, optimizing the range of the initialization. Numerical...
The purpose of this paper is to present and evaluate an improved Naive Bayes algorithm for clustering. Many researchers search for parameter values using EM algorithm. It is well-known that EM approach has a drawback - local optimal solution, so we propose a novel hybrid algorithm of the discrete particle swarm optimization (DPSO) and the EM approach to improve the global search performance. We evaluate...
This paper purposes a novel matching algorithm for image encoding using adaptive classification scheme (ACS) in fractal image compression. It processes based on standard deviation (STD) between range blocks and domain blocks. In this paper, there are two main works, i) the threshold is set to be the ratio of the STD difference and made adaptive ii) we enhance Tong's STD search algorithm by introducing...
Focused on the VRPTW (vehicle routing problem with time windows) and based on SGA (simple genetic algorithm), this paper employs a new IGA (immune genetic algorithm) to solve the VRPTW through using immune operator. This algorithm based on the global searching method of SGA, and using the diversity preservation strategy of antibodies in biology immunity mechanism, the method greatly improves the colony...
The ability to correctly detect the location and derive the contextual information where a concept begins to drift is essential in the study of domains with changing context. This paper proposes a top-down learning method with the incorporation of a learning accuracy mechanism to efficiently detect and manage context changes within a large dataset. With the utilisation of simple search operators to...
According to a problem in the real world, a mathematical model is established for the multi-depot vehicle routing problem with time windows (MDVRPTW). In order to improve the computational efficiency, first, based on decomposition and coordination technology (DCT), the problem is decomposed into several sub-problems and the customers are decomposed into coupling and non-coupling customers by a heuristic...
In this paper, based on the immune network theory, a novel variable neighborhood immune algorithm is proposed for complex function optimization. In the algorithm, a two-level immune network mechanism is suggested to keep the large diversity of populations during the process of population evolutionary, and a variable neighborhood strategy is introduced to overcome the conflict of local search and global...
A novel artificial immune network (AINet) algorithm is proposed in this paper. In the algorithm, a new method is introduced to confirm searching radius, which is based on "the age"-the generations when the cell exists in the network. Moreover, a novel preserving method is proposed to avoid the instability and degradation of the optimal results. These two measures not only increase the local...
This paper proposes a modified particle swarm optimization based on the combining attractive and repulsive operator with function stretching technique (for short MPSOwARS). This new algorithm utilizes adequately the characters that the attractive and repulsive operator can efficiently ensure diversity of swarm and make algorithm prevent premature convergence, and the characters that function stretching...
Exploiting CSP search techniques such as forward checking, arc consistency, dynamic variable ordering, conflict-directed back jumping and local search strategies in the classical Graphplan can effectively avoid the conflicts and the low effect in the process of solution extraction. In this paper, we pay attention to a more complex planning problem - temporal planning problem under the Graphplan framework...
In this paper, a genetic taboo hybrid strategy for PID regulator parameter adaptation is proposed for the belt conveyor driving system. The strategy combines the global search ability of genetic algorithm with the neighborhood search approach of taboo search to find the optimal parameters of the PID regulator in the direct torque control system for mining haulage. Simulation and experiment results...
An attribute reduction method is proposed based on genetic algorithm (GA) with heuristic information. It separates the approximate core attributes from the whole attributes set, then represents the rest of attributes with a group of genetic chromosomes using binary encoding. This improves the local searching ability of GA in the process of global optimizing. Furthermore, the method designs the fitness...
This paper presents a new dynamic method of subpopulation in solving multi-modal search problems with evolutionary algorithms. The new method identify the modes found at each generation and equalises the subpopulation sizes assigned to each mode. Modes are identified sequentially starting with the highest fitness mode. Mode membership is determined by successive grouping of fitness dominated convex...
In this paper, a new ant colony optimization (ACO) that immunity is introduced to is proposed. The proposed algorithm extracts the vaccine from transcendental knowledge and injects it into the elite of ants, which improves the elite ant's capability and makes an improvement of ACO. This paper not only describes the new algorithm's flow, but also makes a simulation. The simulation results show that...
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