• Title/Summary/Keyword: BPSO

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High Utility Itemset Mining by Using Binary PSO Algorithm with V-shaped Transfer Function and Nonlinear Acceleration Coefficient Strategy

  • Tao, Bodong;Shin, Ok Keun;Park, Hyu Chan
    • Journal of information and communication convergence engineering
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    • v.20 no.2
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    • pp.103-112
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    • 2022
  • The goal of pattern mining is to identify novel patterns in a database. High utility itemset mining (HUIM) is a research direction for pattern mining. This is different from frequent itemset mining (FIM), which additionally considers the quantity and profit of the commodity. Several algorithms have been used to mine high utility itemsets (HUIs). The original BPSO algorithm lacks local search capabilities in the subsequent stage, resulting in insufficient HUIs to be mined. Compared to the transfer function used in the original PSO algorithm, the V-shaped transfer function more sufficiently reflects the probability between the velocity and position change of the particles. Considering the influence of the acceleration factor on the particle motion mode and trajectory, a nonlinear acceleration strategy was used to enhance the search ability of the particles. Experiments show that the number of mined HUIs is 73% higher than that of the original BPSO algorithm, which indicates better performance of the proposed algorithm.

Dorsal Hand Vein Identification Based on Binary Particle Swarm Optimization

  • Benziane, Sarah Hachemi;Benyettou, Abdelkader
    • Journal of Information Processing Systems
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    • v.13 no.2
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    • pp.268-284
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    • 2017
  • The dorsal hand vein biometric system developed has a main objective and specific targets; to get an electronic signature using a secure signature device. In this paper, we present our signature device with its different aims; respectively: The extraction of the dorsal veins from the images that were acquired through an infrared device. For each identification, we need the representation of the veins in the form of shape descriptors, which are invariant to translation, rotation and scaling; this extracted descriptor vector is the input of the matching step. The optimization decision system settings match the choice of threshold that allows accepting/rejecting a person, and selection of the most relevant descriptors, to minimize both FAR and FRR errors. The final decision for identification based descriptors selected by the PSO hybrid binary give a FAR =0% and FRR=0% as results.

A Novel Approach for the Unit Commitment with Vehicle-to-grid

  • Jin, Lei;Yang, Huan;Zhou, Yuying;Zhao, Rongxiang
    • Journal of international Conference on Electrical Machines and Systems
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    • v.2 no.3
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    • pp.367-374
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    • 2013
  • The electrical vehicles (EV) with vehicle-to-grid (V2G) capability can be used as loads, energy sources and energy storage in MicroGrid integrated with renewable energy sources. The output power of generators will be reallocated in the considering of V2G. An intelligent unit commitment (UC) with V2G for cost optimization is presented in this paper. A new constraint of UC with V2G is considered to satisfy daily use of EVs. A hybrid optimiza-tion algorithm combined Binary Particle Swarm Optimization (BPSO) with Lagrange Mul-tipliers Method (LMM) is proposed. The difference between results of UC with V2G and UC without V2G is presented.