18 research outputs found

    Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History

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    A hybrid coevolution particle swarm optimization algorithm with dynamic multispecies strategy based on K-means clustering and nonrevisit strategy based on Binary Space Partitioning fitness tree (called MCPSO-PSH) is proposed. Previous search history memorized into the Binary Space Partitioning fitness tree can effectively restrain the individuals’ revisit phenomenon. The whole population is partitioned into several subspecies and cooperative coevolution is realized by an information communication mechanism between subspecies, which can enhance the global search ability of particles and avoid premature convergence to local optimum. To demonstrate the power of the method, comparisons between the proposed algorithm and state-of-the-art algorithms are grouped into two categories: 10 basic benchmark functions (10-dimensional and 30-dimensional), 10 CEC2005 benchmark functions (30-dimensional), and a real-world problem (multilevel image segmentation problems). Experimental results show that MCPSO-PSH displays a competitive performance compared to the other swarm-based or evolutionary algorithms in terms of solution accuracy and statistical tests

    A Novel Plant Root Foraging Algorithm for Image Segmentation Problems

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    This paper presents a new type of biologically-inspired global optimization methodology for image segmentation based on plant root foraging behavior, namely, artificial root foraging algorithm (ARFO). The essential motive of ARFO is to imitate the significant characteristics of plant root foraging behavior including branching, regrowing, and tropisms for constructing a heuristic algorithm for multidimensional and multimodal problems. A mathematical model is firstly designed to abstract various plant root foraging patterns. Then, the basic process of ARFO algorithm derived in the model is described in details. When tested against ten benchmark functions, ARFO shows the superiority to other state-of-the-art algorithms on several benchmark functions. Further, we employed the ARFO algorithm to deal with multilevel threshold image segmentation problem. Experimental results of the new algorithm on a variety of images demonstrated the suitability of the proposed method for solving such problem

    Discrete and Continuous Optimization Based on Hierarchical Artificial Bee Colony Optimizer

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    This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization (HABC), to tackle complex high-dimensional problems. In the proposed multilevel model, the higher-level species can be aggregated by the subpopulations from lower level. In the bottom level, each subpopulation employing the canonical ABC method searches the part-dimensional optimum in parallel, which can be constructed into a complete solution for the upper level. At the same time, the comprehensive learning method with crossover and mutation operator is applied to enhance the global search ability between species. Experiments are conducted on a set of 20 continuous and discrete benchmark problems. The experimental results demonstrate remarkable performance of the HABC algorithm when compared with other six evolutionary algorithms

    The Impact of Atmosphere on Energetics of Lead Halide Perovskites

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    Solar cells based on metal halide perovskites have emerged as a promising low-cost photovoltaic technology. In contrast to inert atmospheres where most of the lab-scale devices are made to date, large-area low-cost production of perovskite solar cells often involves processing of perovskites in various atmospheres including ambient air, nitrogen, and/or vacuum. Herein, the impact of atmosphere on the energy levels of methylammonium lead halide perovskite films is systematically investigated. The atmosphere is varied to simulate the typical fabrication process. Through a comprehensive analysis combining the Fermi level evolution, surface photovoltage, photoluminescence properties, photovoltaic performance, and device simulation, an overall landscape of the energy diagram of the perovskite layer is able to be determined. The findings have direct implications for real-world devices under typical atmospheres, and provide insights into the fabrication-process design and optimization. Furthermore, a universal Fermi level shift under vacuum for lead halide-based perovskites revealed in this study, urges a refreshed view on the energetics studies conducted without considering the atmospheric effect

    A holistic approach to interface stabilization for efficient perovskite solar modules with over 2,000-hour operational stability

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    The upscaling of perovskite solar cells to module scale and long-term stability have been recognized as the most important challenges for the commercialization of this emerging photovoltaic technology. In a perovskite solar module, each interface within the device contributes to the efficiency and stability of the module. Here, we employed a holistic interface stabilization strategy by modifying all the relevant layers and interfaces, namely the perovskite layer, charge transporting layers and device encapsulation, to improve the efficiency and stability of perovskite solar modules. The treatments were selected for their compatibility with low-temperature scalable processing and the module scribing steps. Our unencapsulated perovskite solar modules achieved a reverse-scan efficiency of 16.6% for a designated area of 22.4 cm². The encapsulated perovskite solar modules, which show efficiencies similar to the unencapsulated one, retained approximately 86% of the initial performance after continuous operation for 2,000 h under AM1.5G light illumination, which translates into a T₉₀ lifetime (the time over which the device efficiency reduces to 90% of its initial value) of 1,570 h and an estimated T80 lifetime (the time over which the device efficiency reduces to 80% of its initial value) of 2,680 h

    A Butterfly-Shaped Wideband Microstrip Patch Antenna for Wireless Communication

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    A novel butterfly-shaped patch antenna for wireless communication is introduced in this paper. The antenna is designed for wideband wireless communications and radio-frequency identification (RFID) systems. Two symmetrical quasi-circular arms and two symmetrical round holes are incorporated into the patch of a microstrip antenna to expand its bandwidth. The diameter and position of the circular slots are optimized to achieve a wide bandwidth. The validity of the design concept is demonstrated by means of a prototype having a bandwidth of about 40.1%. The return loss of the butterfly-shaped antenna is greater than 10 dB between 4.15 and 6.36 GHz. The antenna can serve simultaneously most of the modern wireless communication standards

    Hierarchical Artificial Bee Colony Optimizer with Divide-and-Conquer and Crossover for Multilevel Threshold Image Segmentation

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    This paper presents a novel optimization algorithm, namely, hierarchical artificial bee colony optimization (HABC), for multilevel threshold image segmentation, which employs a pool of optimal foraging strategies to extend the classical artificial bee colony framework to a cooperative and hierarchical fashion. In the proposed hierarchical model, the higher-level species incorporates the enhanced information exchange mechanism based on crossover operator to enhance the global search ability between species. In the bottom level, with the divide-and-conquer approach, each subpopulation runs the original ABC method in parallel to part-dimensional optimum, which can be aggregated into a complete solution for the upper level. The experimental results for comparing HABC with several successful EA and SI algorithms on a set of benchmarks demonstrated the effectiveness of the proposed algorithm. Furthermore, we applied the HABC to the multilevel image segmentation problem. Experimental results of the new algorithm on a variety of images demonstrated the performance superiority of the proposed algorithm
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