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Compressive strength prediction and optimization design of sustainable concrete based on squirrel searchalgorithm-extreme gradient boosting technique

《结构与土木工程前沿（英文）》页码 1310-1325 doi: 10.1007/s11709-023-0997-3

摘要： Concrete is the most commonly used construction material. However, its production leads to high carbon dioxide (CO₂) emissions and energy consumption. Therefore, developing waste-substitutable concrete components is necessary. Improving the sustainability and greenness of concrete is the focus of this research. In this regard, 899 data points were collected from existing studies where cement, slag, fly ash, superplasticizer, coarse aggregate, and fine aggregate were considered potential influential factors. The complex relationship between influential factors and concrete compressive strength makes the prediction and estimation of compressive strength difficult. Instead of the traditional compressive strength test, this study combines five novel metaheuristic algorithms with extreme gradient boosting (XGB) to predict the compressive strength of green concrete based on fly ash and blast furnace slag. The intelligent prediction models were assessed using the root mean square error (RMSE), coefficient of determination (R²), mean absolute error (MAE), and variance accounted for (VAF). The results indicated that the squirrel search algorithm-extreme gradient boosting (SSA-XGB) yielded the best overall prediction performance with R² values of 0.9930 and 0.9576, VAF values of 99.30 and 95.79, MAE values of 0.52 and 2.50, RMSE of 1.34 and 3.31 for the training and testing sets, respectively. The remaining five prediction methods yield promising results. Therefore, the developed hybrid XGB model can be introduced as an accurate and fast technique for the performance prediction of green concrete. Finally, the developed SSA-XGB considered the effects of all the input factors on the compressive strength. The ability of the model to predict the performance of concrete with unknown proportions can play a significant role in accelerating the development and application of sustainable concrete and furthering a sustainable economy.

关键词： sustainable concrete fly ash slay extreme gradient boosting technique squirrel search algorithm parametric analysis

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Solving unit commitment problem using a novel version of harmony search algorithm

Roozbeh MORSALI,Tohid JAFARI,Amirhossein GHODS,Mohammad KARIMI

《能源前沿（英文）》 2014年第8卷第3期页码 297-304 doi: 10.1007/s11708-014-0309-7

摘要： In this context, a novel structure was proposed for improving harmony search (HS) algorithm to solve the unit comment (UC) problem. The HS algorithm obtained optimal solution for defined objective function by improvising, updating and checking operators. In the proposed improved self-adaptive HS (SGHS) algorithm, two important control parameters were adjusted to reach better solution from the simple HS algorithm. The objective function of this study consisted of operation, start-up and shut-down costs. To confirm the effectiveness, the SGHS algorithm was tested on systems with 10, 20, 40 and 60 generating units, and the obtained results were compared with those of the simple HS algorithm and other related works.

关键词： generation scheduling harmony search (HS) algorithm intelligent technique unit commitment

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一种改进的和声搜索算法及其在权重模糊产生式规则获取中的应用 Research Article

叶绍强1,周恺卿1,Azlan Mohd ZAIN2,王方岭1,Yusliza YUSOFF2

《信息与电子工程前沿（英文）》 2023年第24卷第11期页码 1574-1590 doi: 10.1631/FITEE.2200334

摘要：和声搜索算法(harmony search, HS)是一种随机元启发式算法，其灵感来自于音乐家的即兴创作过程。针对HS在求解中易陷入局部极值等不足，本文提出一种混合布谷鸟算子的改进的和声布谷鸟搜索算法(modified HS with a hybrid cuckoo search (CS) operator,

关键词：和声搜索算法；布谷鸟搜索算法；全局收敛；函数优化；权重模糊产生式规则抽取

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Optimal design of double-layer barrel vaults using genetic and pattern search algorithms and optimized

《结构与土木工程前沿（英文）》 2023年第17卷第3期页码 378-395 doi: 10.1007/s11709-022-0899-9

摘要： This paper presents a combined method based on optimized neural networks and optimization algorithms to solve structural optimization problems. The main idea is to utilize an optimized artificial neural network (OANN) as a surrogate model to reduce the number of computations for structural analysis. First, the OANN is trained appropriately. Subsequently, the main optimization problem is solved using the OANN and a population-based algorithm. The algorithms considered in this step are the arithmetic optimization algorithm (AOA) and genetic algorithm (GA). Finally, the abovementioned problem is solved using the optimal point obtained from the previous step and the pattern search (PS) algorithm. To evaluate the performance of the proposed method, two numerical examples are considered. In the first example, the performance of two algorithms, OANN + AOA + PS and OANN + GA + PS, is investigated. Using the GA reduces the elapsed time by approximately 50% compared with using the AOA. Results show that both the OANN + GA + PS and OANN + AOA + PS algorithms perform well in solving structural optimization problems and achieve the same optimal design. However, the OANN + GA + PS algorithm requires significantly fewer function evaluations to achieve the same accuracy as the OANN + AOA + PS algorithm.

关键词： optimization surrogate models artificial neural network SAP2000 genetic algorithm

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一种新的融合本体和主机信息的改进禁忌搜索算法的主题爬虫方法 Research Article

刘景发1,王震1,2,钟国1,杨志和1

《信息与电子工程前沿（英文）》 2023年第24卷第6期页码 859-875 doi: 10.1631/FITEE.2200315

摘要：为解决传统主题爬虫方法存在的主题描述不完整和重复爬取已访问链接的问题，本文提出一种新的融合本体和主机信息的改进禁忌搜索算法的主题爬虫方法（FCITS_OH）。该方法基于形式概念分析（FCA）构建领域本体，在语义和知识层面描述主题。为避免重复爬取已访问的链接和扩大搜索范围，提出一种改进的禁忌搜索（ITS）算法和记忆主机信息的策略。此外，为改进未访问链接的主题相关性的评估方法，提出一种基于Web文本和链接结构的综合优先度评估方法。以旅游和暴雨灾害为主题的实验结果表明，对于不同的性能指标，所提出的爬虫方法优于文献中其它主题爬虫策略。

关键词：主题爬虫；禁忌搜索算法；本体；主机信息；优先度评估

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A simple multi-wave algorithm for the uncapacitated facility location problem

Fred GLOVER, Saïd HANAFI, Oualid GUEMRI, Igor CREVITS

《工程管理前沿（英文）》 2018年第5卷第4期页码 451-465 doi: 10.15302/J-FEM-2018038

摘要：

The multi-wave algorithm (Glover, 2016) integrates tabu search and strategic oscillation utilizing repeated waves (nested iterations) of constructive search or neighborhood search. We propose a simple multi-wave algorithm for solving the Uncapacitated Facility Location Problem (UFLP) to minimize the combined costs of selecting facilities to be opened and of assigning each customer to an opened facility in order to meet the customers’ demands. The objective is to minimize the overall cost including the costs of opening facilities and the costs of allocations. Our experimental tests on a standard set of benchmarks for this widely-studied class of problems show that our algorithm outperforms all previous methods.

关键词： discrete optimization UFLP multi-wave optimization strategic oscillation tabu search

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MSSSA：一种针对全局优化问题的多策略增强型麻雀搜索算法 Research Article

孟凯1,2,陈晨1,2,辛斌1,2

《信息与电子工程前沿（英文）》 2022年第23卷第12期页码 1828-1847 doi: 10.1631/FITEE.2200237

摘要：麻雀搜索算法(SSA)是一种新的元启发式优化方法，具有简单和灵活的优点。然而，在处理多模态优化问题时，该算法仍存在早熟收敛、探索与开发不平衡等缺陷。针对上述问题，本文提出一种多策略增强的麻雀搜索算法(MSSSA)。首先，引入混沌映射以获取高质量的初始种群，并采用对立学习策略增加种群的多样性。其次，设计了一种自适应参数控制策略，以在全局探索与局部开发之间保持适当的平衡。最后，在个体更新阶段嵌入混合扰动机制，以避免算法陷入局部最优。为了验证所提方法的有效性，在IEEE CEC2014和IEEE CEC2019测试集的40个函数，以及10个不同维度的经典函数上进行了大量的实验。实验结果表明，与一些先进的算法相比，所提出的MSSSA表现出突出的优化性能。该算法还成功地应用于两个工程优化问题，证明了MSSSA在解决实际问题方面的优越性。

关键词：群智能；麻雀搜索算法；自适应参数控制策略；混合扰动机制；优化问题

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基于嵌入协作的多方法协作优化方法

罗文彩,罗世彬,王振国

《中国工程科学》 2004年第6卷第4期页码 51-55

摘要：

提出一种基于嵌入协作的多方法协作优化方法。算法采用嵌入方式组织各个优化方法之间的协作，利用优化方法之间的协作效应提高优化性能。进行遗传算法、模式搜索法和Powell法嵌入协作组成的多方法协作优化方法设计。计算实例表明，基于嵌入协作的多方法协作优化方法取得了优于单个优化方法的全局最优特性。

关键词：多方法协作优化方法嵌入协作遗传算法模式搜索法 Powell法

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一种改进的果蝇优化算法及其在旅行商问题求解中的应用 Article

Lan HUANG, Gui-chao WANG, Tian BAI, Zhe WANG

《信息与电子工程前沿（英文）》 2017年第18卷第10期页码 1525-1533 doi: 10.1631/FITEE.1601364

摘要：旅行商问题（traveling salesman problem, TSP）是经典的NP（non-deterministic polynomial）难问题，在实际工程中有许多应用。而果蝇优化算法作为一种用于求解TSP问题的新群智能算法，具有易于理解、实现简单等优点。然而，该算法收敛速度慢、易陷入局部最优，从而导致寻优精度不高。为了有效求解TSP问题，本文提出了三种改进方法，以优化果蝇算法在TSP求解中的应用。一是，更加注重果蝇觅食行为中的视觉搜索能力，从而增强果蝇算法的收敛能力；二是，在果蝇优化算法中融入了淘汰机制以增加种群多样性；三是，提出了逆序操作算子和乘法操作算子，并将这两种基本操作算子运用到果蝇算法求解TSP问题上。本文对TSPLIB中的10个算例进行仿真实验，并与其它算法的实验结果进行对比，结果证明该算法不仅收敛速度快，而且寻优精度高。

关键词：旅行商问题；果蝇优化算法；淘汰机制；视觉搜索；操作算子

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Organizational dynamics in adaptive distributed search processes: effects on performance and the role

Friederike WALL

《信息与电子工程前沿（英文）》 2016年第17卷第4期页码 283-295 doi: 10.1631/FITEE.1500306

摘要： In this paper, the effects of altering the organizational setting of distributed adaptive search processes in the course of search are investigated. We put particular emphasis on the complexity of interactions between partial search problems assigned to search agents. Employing an agent-based simulation based on the framework of NK landscapes we analyze different temporal change modes of the organizational set-up. The organizational properties under change include, for example, the coordination mechanisms among search agents. Results suggest that inducing organizational dynamics has the potential to increase the effectiveness of distributed adaptive search processes with respect to various performance measures like the final performance achieved at the end of the search, the chance to find the optimal solution of the search problem, or the average performance per period achieved during the search process. However, results also indicate that the mode of temporal change in conjunction with the complexity of the search problem considerably affects the order of magnitude of these beneficial effects. In particular, results suggest that organizational dynamics induces a shift towards more exploration, i.e., discovery of new areas in the fitness landscape, and less exploitation, i.e., stepwise improvement.

关键词： Agent-based simulation Complexity Coordination Distributed search NK landscapes

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一种使用静态分析和遗传搜索在Android恶意软件检测中搜索最优特征的方法 None

Ahmad FIRDAUS, Nor Badrul ANUAR, Ahmad KARIM, Mohd Faizal Ab RAZAK

《信息与电子工程前沿（英文）》 2018年第19卷第6期页码 712-736 doi: 10.1631/FITEE.1601491

摘要：移动设备制造商在全球范围内快速开发各种Android版本。同时，网络罪犯也在实施各种恶意行为，例如跟踪用户活动、窃取个人数据以及实施银行诈骗。由于在日常生活中使用Android进行重要通信的人群数量庞大，这些网络罪犯从中获得了巨大非法收益。为此，安全从业者通过静态和动态分析对恶意软件进行识别。静态分析具有整体代码覆盖、低资源消耗和快速处理的优势。然而，静态分析需要最少量的特征才能对恶意软件进行有效分类。因此，我们采用基于遗传算法（GA）的遗传搜索（GS）在106个字符串中选择特征。为评估由GS确定的最佳特征，我们使用了5种机器学习分类器，分别是Naïve Bayes（NB）、功能树（FT）、J48、随机森林（RF）和多层感知器（MLP）。在这5种分类器中，FT仅使用6种特征，获得最高准确度（95％）和最高真正率（TPR）（96.7％）。

关键词：遗传算法；静态分析；Android；恶意软件；机器学习

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脉冲水射流水力共振设计

蒲家宁,陈明

《中国工程科学》 2009年第11卷第2期页码 36-42

摘要：

在导管首端设置正弦脉冲流发生器，下游某处设置空气室，精心构建系统条件造成水力共振，使喷嘴处脉冲射流的压力振幅大大提高。系统的数学物理模型用水力瞬变特征线有限差分方程建立，变时步方法解算。最优水力共振条件用Matlab直接搜索算法搜寻。正弦脉冲流发生器由恒流泵和正弦容积变化活塞缸构成，电动活塞泵用凸轮传动给出恒定流量，活塞缸活塞用凸轮或曲轴连杆传动使缸容正弦变化。

关键词：脉冲水射流水力共振特征线解法变时步法 Matlab 直接搜寻算法正弦脉冲流发生器

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基于自适应文化基因算法的无人机搜救规划 Research Articles

洪立斌1,王玥2,杜怡辰2,陈鑫1,郑宇军1

《信息与电子工程前沿（英文）》 2021年第22卷第11期页码 1477-1491 doi: 10.1631/FITEE.2000632

摘要：无人机在搜救任务中的应用日益广泛，然而由于响应时间有限、搜索区域广、搜索模式多样，无人机搜索规划也更加复杂。本文提出一类无人机搜索规划问题，其搜索区域被划分为一组子区域，且每个子区域中目标存在的先验概率已知。解决该问题需要确定这些子区域的搜索顺序以及每个子区域的搜索模式，使得最终搜索成功的概率最大化。提出一种自适应文化基因算法，它结合了遗传算法和一组邻域搜索策略，基于问题求解过程中的适应度提升和多样性提升指标，动态选择邻域搜索策略。在多个问题实例上的计算实验表明，与先进的全局搜索启发式算法以及非自适应文化基因算法相比，所提算法展现了出色性能。

关键词：文化基因算法；自适应；无人机；搜救

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基于修正模拟退火算法及溢出面积模型的固定边界布图规划 Article

De-xuan ZOU,Gai-ge WANG,Gai PAN,Hong-wei QI

《信息与电子工程前沿（英文）》 2016年第17卷第11期页码 1228-1244 doi: 10.1631/FITEE.1500386

摘要：第一，提出了一种修正模拟退火算法（Modified simulated annealing algorithm, MSA）。

关键词：固定边界布图规划；修正的模拟退火算法；全局搜索；溢出面积模型；B*-tree表示法

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Border-search and jump reduction method for size optimization of spatial truss structures

Babak DIZANGIAN, Mohammad Reza GHASEMI

《结构与土木工程前沿（英文）》 2019年第13卷第1期页码 123-134 doi: 10.1007/s11709-018-0478-2

摘要： This paper proposes a sensitivity-based border-search and jump reduction method for optimum design of spatial trusses. It is considered as a two-phase optimization approach, where at the first phase, the first local optimum is found by few analyses, after the whole searching space is limited employing an efficient random strategy, and the second phase involves finding a sequence of local optimum points using the variables sensitivity with respect to corresponding values of constraints violation. To reach the global solution at phase two, a sequence of two sensitivity-based operators of border-search operator and jump operator are introduced until convergence is occurred. Sensitivity analysis is performed using numerical finite difference method. To do structural analysis, a link between open source software of OpenSees and MATLAB was developed. Spatial truss problems were attempted for optimization in order to show the fastness and efficiency of proposed technique. Results were compared with those reported in the literature. It shows that the proposed method is competitive with the other optimization methods with a significant reduction in number of analyses carried.

关键词： optimum design sensitivity analysis reduction method spatial trusses OpenSees