Static software defect prediction problem is one crucial problem in software test, to measure the performance, several indexes are introduced. In this paper, a two-objective software defect prediction model is employe...
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One of basic problems of multi-target search in swarm robotics is how to allocate the tasks of searching targets among robots. In this paper, the formal description of the problem of multi-target search and task alloc...
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Lennard-Jones (LJ) cluster is one important problem in chemistry, materials and physics. The main difficulty is the amount of local optima. Recently, an Artificial Plant Photosynthesis and Phototropism Mechanism (APPM...
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The problem of protein folding structure prediction is a classical NP problem. In this paper, we present a new hybrid artificial plant optimization algorithm, in which one new golden section operator is designed to mi...
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Software defection prediction is not only crucial for improving software quality, but also helpful for software test effort estimation. As is well- known,80%of the fault happens in20%of the modules. Therefore,we need ...
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Support vector machine (SVM) model is becoming an increasingly popular method in software defects prediction. This model has strong non-linear classifying ability. However, SVM model lacks effective method to determin...
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Artificial plant optimization algorithm (APOA) is a population-based stochastic optimization algorithm by simulating the plant growing mechanism. In the standard version, there is no furcation in each branch. This phe...
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Artificial plant optimization algorithm (APOA) is a population-based stochastic optimization algorithm by simulating the plant growing mechanism. In the standard version, there is no furcation in each branch. This phenomenon is confused with the natural tree because in natural tree, each branch maintains many furcations to improve the efficiency of photosynthesis. To avoid this shortcoming, we incorporate two selection strategies into the methodology of the standard version, and propose one new variant called artificial plant optimization algorithm with double selection strategies. Furthermore, to investigate the performance, this new algorithm is applied to optimize the DV-Hop location algorithm. Simulation results show it achieves the better performance than DV-Hop.
A variant of Grey wolf optimizer(GWO),called grey wolf optimizer with Ranking-based mutation operator(RGWO) is applied to the Infinite impulse response(IIR) system identification problem. RGWO makes GWO faster and mor...
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A variant of Grey wolf optimizer(GWO),called grey wolf optimizer with Ranking-based mutation operator(RGWO) is applied to the Infinite impulse response(IIR) system identification problem. RGWO makes GWO faster and more robust. In RGWO, the rankingbased mutation operator is integrated into the GWO to accelerate the convergence speed, and thus enhance the performance. The simulation results over several models are presented and statistically validated. Compared to other robust evolutionary algorithms, RGWO performs significantly better in terms of the quality, speed, and the stability of the final solutions.
Group-decided Watts-Strogatz Particle Swarm Optimisation (GWSPSO) is a new novel variant of Particle Swarm Optimisation (PSO) that aims to enhance the escaping capability from local optimum by incorporating group deci...
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In the process of urban water resources planning, the demand estimation of urban water consumption is one of the important basic contents. In this paper, a hybrid model of linear estimation model and an exponential es...
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