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Novel quantum-inspired firefly algorithm for optimal power quality monitor placement

Ling Ai WONG,Hussain SHAREEF,Azah MOHAMED,Ahmad Asrul IBRAHIM

《能源前沿（英文）》 2014年第8卷第2期页码 254-260 doi: 10.1007/s11708-014-0302-1

摘要： The application of a quantum-inspired firefly algorithm was introduced to obtain optimal power quality monitor placement in a power system. The conventional binary firefly algorithm was modified by using quantum principles to attain a faster convergence rate that can improve system performance and to avoid premature convergence. In the optimization process, a multi-objective function was used with the system observability constraint, which is determined via the topological monitor reach area concept. The multi-objective function comprises three functions: number of required monitors, monitor overlapping index, and sag severity index. The effectiveness of the proposed method was verified by applying the algorithm to an IEEE 118-bus transmission system and by comparing the algorithm with others of its kind.

关键词： quantum-inspired binary firefly algorithm topological monitor reach area power quality

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基于量子元胞自动机的可逆二进制减法器设计 Article

Jadav Chandra DAS, Debashis DE

《信息与电子工程前沿（英文）》 2017年第18卷第9期页码 1416-1429 doi: 10.1631/FITEE.1600999

摘要：在纳米技术领域，量子元胞自动机（quantum dot-cellular automata, QCA）可作为传统互补金属氧化物半导体（complementary metal oxide semiconductor

关键词：量子元胞自动机（quantum dot-cellular automata QCA）；可逆逻辑；DG门；二进制减法器；量子成本

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Combined heat and power economic dispatch problem using firefly algorithm

Afshin YAZDANI, T. JAYABARATHI, V. RAMESH, T. RAGHUNATHAN

《能源前沿（英文）》 2013年第7卷第2期页码 133-139 doi: 10.1007/s11708-013-0248-8

摘要： Cogeneration units, which produce both heat and electric power, are found in many process industries. These industries also consume heat directly in addition to electricity. The cogeneration units operate only within a feasible zone. Each point within the feasible zone consists of a specific value of heat and electric power. These units are used along with other units, which produce either heat or power exclusively. Hence, the economic dispatch problem for these plants to optimize the fuel cost is quite complex and several classical and meta-heuristic algorithms have been proposed earlier. This paper applies the firefly algorithm, which is inspired by the behavior of fireflies which attract each other based on their luminosity. The results obtained have been compared with those obtained by other methods earlier and showed a marked improvement over the earlier methods.

关键词： combined heat and power (CHP) economic dispatch meta-heuristic algorithm firefly algorithm cogeneration

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A new systematic firefly algorithm for forecasting the durability of reinforced recycled aggregate concrete

Wafaa Mohamed SHABAN; Khalid ELBAZ; Mohamed AMIN; Ayat gamal ASHOUR

《结构与土木工程前沿（英文）》 2022年第16卷第3期页码 329-346 doi: 10.1007/s11709-022-0801-9

摘要： This study presents a new systematic algorithm to optimize the durability of reinforced recycled aggregate concrete. The proposed algorithm integrates machine learning with a new version of the firefly algorithm called chaotic based firefly algorithm (CFA) to evolve a rational and efficient predictive model. The CFA optimizer is augmented with chaotic maps and Lévy flight to improve the firefly performance in forecasting the chloride penetrability of strengthened recycled aggregate concrete (RAC). A comprehensive and credible database of distinctive chloride migration coefficient results is used to establish the developed algorithm. A dataset composite of nine effective parameters, including concrete components and fundamental characteristics of recycled aggregate (RA), is used as input to predict the migration coefficient of strengthened RAC as output. k-fold cross validation algorithm is utilized to validate the hybrid algorithm. Three numerical benchmark analyses are applied to prove the superiority and applicability of the CFA algorithm in predicting chloride penetrability. Results show that the developed CFA approach significantly outperforms the firefly algorithm on almost tested functions and demonstrates powerful prediction. In addition, the proposed strategy can be an active tool to recognize the contradictions in the experimental results and can be especially beneficial for assessing the chloride resistance of RAC.

关键词： chloride penetrability recycled aggregate concrete machine learning concrete components durability

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基于蛙跳思想的量子编码遗传算法

许波,彭志平,余建平,柯文德

《中国工程科学》 2014年第16卷第3期页码 108-112

摘要：

量子门旋转相位、变异概率大小的确定，是目前制约量子遗传算法效率的两个主要问题。本文提出一种基于蛙跳思想的量子编码遗传算法（QRGA），该算法采用自适应的方式对量子旋转门旋转角进行调整，并基于模糊逻辑将蛙跳的步长进行量化以指导变异概率调整，保证进化的方向性和提高算法效率，对比实验结果表明算法可以避免陷入局部最优解，并能快速收敛到全局最优解，在运行时间和解的性能上都取得了较好的效果。

关键词：量子编码量子遗传算法蛙跳算法群体智能

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Assessment of novel nature-inspired fuzzy models for predicting long contraction scouring and related

《结构与土木工程前沿（英文）》 2021年第15卷第3期页码 665-681 doi: 10.1007/s11709-021-0713-0

摘要： The scouring phenomenon is one of the major problems experienced in hydraulic engineering. In this study, an adaptive neuro-fuzzy inference system is hybridized with several evolutionary approaches, including the ant colony optimization, genetic algorithm, teaching-learning-based optimization, biogeographical-based optimization, and invasive weed optimization for estimating the long contraction scour depth. The proposed hybrid models are built using non-dimensional information collected from previous studies. The proposed hybrid intelligent models are evaluated using several statistical performance metrics and graphical presentations. Besides, the uncertainty of models, variables, and data are inspected. Based on the achieved modeling results, adaptive neuro-fuzzy inference system–biogeographic based optimization (ANFIS-BBO) provides superior prediction accuracy compared to others, with a maximum correlation coefficient (R_test = 0.923) and minimum root mean square error value (RMSE_test = 0.0193). Thus, the proposed ANFIS-BBO is a capable cost-effective method for predicting long contraction scouring, thus, contributing to the base knowledge of hydraulic structure sustainability.

关键词： long contraction scour prediction uncertainty ANFIS model meta-heuristic algorithm

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动态二叉树表示环境的A^*算法及其在足球机器人路径规划中的实现

唐平,杨宜民

《中国工程科学》 2002年第4卷第9期页码 50-53

摘要：

提出采用二叉树表示二维空间的方法，对全局路径规划和局部路径规划进行综合考虑，设计移动机器人在复杂环境下对动态障碍物进行避障的A^*算法。在足球机器人系统中进行仿真，将二叉树动态地表示球场的机器人与目标为对角线的矩型环境，使搜索范围随搜索进程动态地减小，实现了路径规划的整体优化。

关键词：动态二叉树 A^*算法路径规划

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A new technique for solving the multi-objective optimization problem using hybrid approach

Mimoun YOUNES,Khodja FOUAD,Belabbes BAGDAD

《能源前沿（英文）》 2014年第8卷第4期页码 490-503 doi: 10.1007/s11708-014-0311-0

摘要： Energy efficiency, which consists of using less energy or improving the level of service to energy consumers, refers to an effective way to provide overall energy. But its increasing pressure on the energy sector to control greenhouse gases and to reduce CO emissions forced the power system operators to consider the emission problem as a consequential matter besides the economic problems. The economic power dispatch problem has, therefore, become a multi-objective optimization problem. Fuel cost, pollutant emissions, and system loss should be minimized simultaneously while satisfying certain system constraints. To achieve a good design with different solutions in a multi-objective optimization problem, fuel cost and pollutant emissions are converted into single optimization problem by introducing penalty factor. Now the power dispatch is formulated into a bi-objective optimization problem, two objectives with two algorithms, firefly algorithm for optimization the fuel cost, pollutant emissions and the real genetic algorithm for minimization of the transmission losses. In this paper the new approach (firefly algorithm-real genetic algorithm, FFA-RGA) has been applied to the standard IEEE 30-bus 6-generator. The effectiveness of the proposed approach is demonstrated by comparing its performance with other evolutionary multi-objective optimization algorithms. Simulation results show the validity and feasibility of the proposed method.

关键词： economic power dispatch (EPD) firefly algorithm (FFA) real genetic algorithm (RGA) hybrid method

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改进二进制人工蜂群算法求解多维背包问题

王志刚,夏慧明

《中国工程科学》 2014年第16卷第8期页码 106-112

摘要：

针对二进制人工蜂群算法收敛速度慢、易陷入局部最优的缺点，提出一种改进的二进制人工蜂群算法。新算法对人工蜂群算法中的邻域搜索公式进行了重新设计，并通过Bayes 公式来决定食物源的取值概率。将改进后的算法应用于求解多维背包问题，在求解过程中利用贪婪算法对进化过程中的不可行解进行修复，对背包资源利用不足的可行解进行修正。通过对典型多维背包问题的仿真实验，表明了本文算法在解决多维背包问题上的可行性和有效性。

关键词：人工蜂群算法多维背包问题贪婪算法组合优化

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量子计算研究现状与未来发展

李晓巍,付祥,燕飞,钟有鹏,陆朝阳,张君华,贺煜,尉石,鲁大为,辛涛,陈济雷,林本川,张振生,刘松,陈远珍,俞大鹏

《中国工程科学》 2022年第24卷第4期页码 133-144 doi: 10.15302/J-SSCAE-2022.04.016

摘要： Quantum computing in the NISQ era and beyond [J]. Quantum , 2018 , 2 : 79 .A fast quantum mechanical algorithm for database search [C].Quantum algorithm for linear systems of equations [J].Neural networks with quantum architecture and quantum learning [J].A quantum approximate optimization algorithm [EBOL]. 2014-11-14 [ 2022-05-15 ].

关键词：量子计算量子算法量子测控系统量子软件超导量子计算分布式量子计算囚禁离子量子计算硅基量子计算光量子计算中性原子量子计算金刚石氮空位色心核磁共振量子计算自旋波量子计算拓扑量子计算

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海豚群算法 Article

Tian-qi WU,Min YAO,Jian-hua YANG

《信息与电子工程前沿（英文）》 2016年第17卷第8期页码 717-729 doi: 10.1631/FITEE.1500287

摘要：群体智能算法采取分布式解决问题的策略，已成功应用于很多传统算法难以解决的优化问题。目前已有粒子群算法、遗传算法、蜂群算法、蚁群算法等已经成功实现且效果良好的算法，但在优化对象日益复杂的今天，这些算法越来越难以满足人们对精度和时间的要求，而改进这些算法所带来的收益也越来越低。在这种情况下，设计一种新的算法来更好地解决优化问题变得越来越有意义。海豚有很多值得关注的生物特性和生活习性，如回声定位、信息交流、合作分工等。通过将这些生物特性和生活习性与群体智能的思想结合起来，引入优化问题中，我们提出了一种新的算法——海豚群算法，并给出了算法的相关定义，详细阐述了算法中搜寻、呼叫、接受、捕猎四个关键阶段。为了验证海豚群算法的效果，使用了10个性质各异的基准函数对海豚群算法以及粒子群算法、遗传算法、蜂群算法进行实验，并将4个函数的收敛速度和基准函数结果进行比较。实验结果表明，海豚群算法在大多数情况下，特别是在低维单峰函数、高维多峰函数、步长函数、带随机变量的函数中表现良好，具有收敛速度先慢后快、阶段性收敛、不易陷入局部最优、对基准函数具体性质没有要求等特点，尤其适用于适应度函数调用次数较多、使用个体较少的优化问题。

关键词：仿生算法；海豚；优化

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二元光学在强激光波面整形中的应用

金国藩,谭峭锋,严瑛白,邬敏贤

《中国工程科学》 2000年第2卷第6期页码 27-32

摘要：

文章首先介绍了二元光学波面整形器件的理论基础。在分析GS、YG等正反迭代算法存在问题的基础上，提出三种优化算法，即全局/局部联合搜索算法（GLUSA）、爬山-模拟退火混合算法及多分辨率的混合优化算法。以惯性约束核聚变中光束匀滑为例，进行了二元光学器件的位相设计，获得了良好的位相结构与焦斑性能。采用旋转镂空掩膜板制作了准连续位相器件，并利用CCD与多种光强衰减片进行焦斑光强测量。实验结果表明：获得了较好的顶部均匀性、陡边、小旁瓣、高主瓣能量利用率以及光斑中心没有锐脉冲的光强分布。

关键词：二元光学波面整型位相器件优化算法

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Improving hole transfer of boron nitride quantum dots modified PDI for efficient photodegradation

《化学科学与工程前沿（英文）》 2023年第17卷第11期页码 1718-1727 doi: 10.1007/s11705-023-2319-7

摘要： In recent years, organic photocatalyst under visible-light absorption has shown significant potential for solving environmental problems. However, it is still a great challenge for constructing a highly active organic photocatalyst due to the low separation efficiency of photogenerated carriers. Herein, an effective and robust photocatalyst perylene-3,4,9,10-tetracarboxylic diamide/boron nitride quantum dots (PDI/BNQDs), consisting of self-assemble PDI with π–π stacking structure and BNQDs, has been constructed and researched under visible light irradiation. The PDI/BNQDs composite gradually increases organic pollutant photodegradation with the loading amount of BNQDs. With 10 mL of BNQDs solution added (PDI/BNQDs-10), the organic pollutant photodegradation performance reaches a maximum, about 6.16 times higher with methylene blue and 1.68 times higher with ciprofloxacin than that of pure PDI supramolecular. The enhancement is attributed to improved separation of photogenerated carriers from self-assembled PDI by BNQDs due to their preeminent ability to extract holes. This work is significant for the supplement of PDI supramolecular composite materials. We believe that this photocatalytic design is capable of expanding organic semiconductors’ potential for their applications in photocatalysis.

关键词： PDI boron nitride quantum dots photocatalysis hole transfer

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用于语音识别的二值神经网络 Regular Papers

Yan-min QIAN, Xu XIANG

《信息与电子工程前沿（英文）》 2019年第20卷第5期页码 701-715 doi: 10.1631/FITEE.1800469

摘要：近年来，在语音识别的声学建模中，深度神经网络(DNNs)明显优于高斯混合模型。然而，推断阶段巨大的计算量使其难以部署在低功耗的嵌入式模型上。为此，稀疏性和低精度定点量化技术被广泛使用。为降低推理阶段计算量，本文开发了用于语音识别的二进制神经网络，并实现了高速的二值矩阵乘法。在中央处理器(CPU)和图形处理单元(GPU)上，二值矩阵乘法的运行速度是浮点矩阵乘法的5–7倍。针对大规模连续语音识别的声学建模，提出多种二值神经网络及相关模型优化算法。为提高二值模型的精度，探索了从浮点模型到二值模型的知识蒸馏技术。在标准的Switchboard语音识别任务上，该二值神经网络模型比浮点神经网络模型速度提高3–4倍。借助知识蒸馏技术，二值深度神经网络或卷积神经网络相对其浮点神经网络的词错误率增加可以保持在15%以内。若只二值化卷积神经网络的卷积层，词错误率增加几乎可忽略。

关键词：语音识别；二值神经网络；二值矩阵乘法；知识蒸馏；位1计数

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基于改进萤火虫算法的雷达网络最优化部署 Regular Papers

Xue-jun ZHANG, Wei JIA, Xiang-min GUAN, Guo-qiang XU, Jun CHEN, Yan-bo ZHU

《信息与电子工程前沿（英文）》 2019年第20卷第3期页码 425-437 doi: 10.1631/FITEE.1800749

摘要：随着无人机行业快速发展，无人机入侵带来的威胁和挑战引起越来越多关注。雷达网络检测是无人机入侵防御的重要手段之一。为在有限雷达资源下形成紧密可靠的雷达监视网络，雷达网优化部署至关重要。然而，由于非线性且变量紧密耦合，雷达网部署优化问题难以解决。提出基于反馈机制的邻居学习策略和精英种群局部搜索策略的改进萤火虫算法，以平衡开发与探索能力，同时采用混沌序列初始化萤火虫位置，提高种群多样性。标准优化测试函数实验和典型雷达部署案例实验表明，该改进萤火虫算法比经典萤火虫算法和4个近期提出的改进算法有更好寻优性能，能有效解决雷达网部署优化问题。

关键词：改进萤火虫算法；雷达监视网络；部署优化；无人机入侵防御

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标题作者时间类型操作

Novel quantum-inspired firefly algorithm for optimal power quality monitor placement

Ling Ai WONG,Hussain SHAREEF,Azah MOHAMED,Ahmad Asrul IBRAHIM

期刊论文

基于量子元胞自动机的可逆二进制减法器设计

Jadav Chandra DAS, Debashis DE

期刊论文

Combined heat and power economic dispatch problem using firefly algorithm

Afshin YAZDANI, T. JAYABARATHI, V. RAMESH, T. RAGHUNATHAN

期刊论文