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期刊论文 10

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2022 1

2021 1

2019 2

2017 1

2014 4

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人工蜂群算法 1

人工蜂群；二进制优化；无容量限制的设施选址位置问题（UFLP） 1

多维背包问题 1

富营养污染物 1

本土植物 1

植物性状 1

氮 1

热带植物 1

生物保留系统 1

磷 1

组合优化 1

贪婪算法 1

雨水 1

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consideration of uncertainties for deployment of distributed energy resources using interactive honey bee

Iraj AHMADIAN,Oveis ABEDINIA,Noradin GHADIMI

《能源前沿（英文）》 2014年 第8卷 第4期   页码 412-425 doi: 10.1007/s11708-014-0315-9

摘要： This paper presents a novel modified interactive honey bee mating optimization (IHBMO) base fuzzy stochastic long-term approach for determining optimum location and size of distributed energy resources (DERs). The Monte Carlo simulation method is used to model the uncertainties associated with long-term load forecasting. A proper combination of several objectives is considered in the objective function. Reduction of loss and power purchased from the electricity market, loss reduction in peak load level and reduction in voltage deviation are considered simultaneously as the objective functions. First, these objectives are fuzzified and designed to be comparable with each other. Then, they are introduced into an IHBMO algorithm in order to obtain the solution which maximizes the value of integrated objective function. The output power of DERs is scheduled for each load level. An enhanced economic model is also proposed to justify investment on DER. An IEEE 30-bus radial distribution test system is used to illustrate the effectiveness of the proposed method.

关键词： component     distributed energy resources     fuzzy optimization     loss reduction     interactive honey bee mating optimization (IHBMO)     voltage deviation reduction     stochastic programming    

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Artificial bee colony optimization for economic dispatch with valve point effect

Yacine LABBI,Djilani Ben ATTOUS,Belkacem MAHDAD

《能源前沿（英文）》 2014年 第8卷 第4期   页码 449-458 doi: 10.1007/s11708-014-0316-8

摘要： In recent years, various heuristic optimization methods have been proposed to solve economic dispatch (ED) problem in power systems. This paper presents the well-known power system ED problem solution considering valve-point effect by a new optimization algorithm called artificial bee colony (ABC). The proposed approach has been applied to various test systems with incremental fuel cost function, taking into account the valve-point effects. The results show that the proposed approach is efficient and robust when compared with other optimization algorithms reported in literature.

关键词： artificial bee colony (ABC) algorithm     economic dispatch (ED)     valve-point effect     optimization    

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An improved artificial bee colony algorithm with MaxTF heuristic rule for two-sided assembly line balancing

Xiaokun DUAN, Bo WU, Youmin HU, Jie LIU, Jing XIONG

《机械工程前沿（英文）》 2019年 第14卷 第2期   页码 241-253 doi: 10.1007/s11465-018-0518-6

摘要： Two-sided assembly line is usually used for the assembly of large products such as cars, buses, and trucks. With the development of technical progress, the assembly line needs to be reconfigured and the cycle time of the line should be optimized to satisfy the new assembly process. Two-sided assembly line balancing with the objective of minimizing the cycle time is called TALBP-2. This paper proposes an improved artificial bee colony (IABC) algorithm with the MaxTF heuristic rule. In the heuristic initialization process, the MaxTF rule defines a new task’s priority weight. On the basis of priority weight, the assignment of tasks is reasonable and the quality of an initial solution is high. In the IABC algorithm, two neighborhood strategies are embedded to balance the exploitation and exploration abilities of the algorithm. The employed bees and onlooker bees produce neighboring solutions in different promising regions to accelerate the convergence rate. Furthermore, a well-designed random strategy of scout bees is developed to escape local optima. The experimental results demonstrate that the proposed MaxTF rule performs better than other heuristic rules, as it can find the best solution for all the 10 test cases. A comparison of the IABC algorithm and other algorithms proves the effectiveness of the proposed IABC algorithm. The results also denote that the IABC algorithm is efficient and stable in minimizing the cycle time for the TALBP-2, and it can find 20 new best solutions among 25 large-sized problem cases.

关键词： two-sided assembly line balancing problem     artificial bee colony algorithm     heuristic rules     time boundary    

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Damage assessment and diagnosis of hydraulic concrete structures using optimization-based machine learning technology

《结构与土木工程前沿（英文）》   页码 1281-1294 doi: 10.1007/s11709-023-0975-9

摘要： Concrete is widely used in various large construction projects owing to its high durability, compressive strength, and plasticity. However, the tensile strength of concrete is low, and concrete cracks easily. Changes in the concrete structure will result in changes in parameters such as the frequency mode and curvature mode, which allows one to effectively locate and evaluate structural damages. In this study, the characteristics of the curvature modes in concrete structures are analyzed and a method to obtain the curvature modes based on the strain and displacement modes is proposed. Subsequently, various indices for the damage diagnosis of concrete structures based on the curvature mode are introduced. A damage assessment method for concrete structures is established using an artificial bee colony backpropagation neural network algorithm. The proposed damage assessment method for dam concrete structures comprises various modal parameters, such as curvature and frequency. The feasibility and accuracy of the model are evaluated based on a case study of a concrete gravity dam. The results show that the damage assessment model can accurately evaluate the damage degree of concrete structures with a maximum error of less than 2%, which is within the required accuracy range of damage identification and assessment for most concrete structures.

关键词： hydraulic structure     curvature mode     damage detection     artifical neural network     artificial bee colony    

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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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面向热带地区植物修复的植物性状研究 Article

Xiangting Cleo Chen, Liling Huang, Tze Hsien Agnes Chang, Bee Lian Ong, Say Leong Ong, Jiangyong Hu

《工程（英文）》 2019年 第5卷 第5期   页码 841-848 doi: 10.1016/j.eng.2019.07.019

摘要：

水是一种有限而宝贵的资源。新加坡的国家水源有4种补给方式，其中之一是自然降水。雨水径流会收集污染物，并将其富集到排水系统和水库中。在当地雨水径流中发现的主要富营养污染物包括硝酸盐和磷酸盐，这些富营养污染物可能导致富营养化。在有植物存在的情况下，生物滞留系统可以有效去除这些污染物。本文探讨了植物特性对雨水径流中营养性污染物的植物修复作用，并将其应用于生物防护系统中。所研究的植物物种在叶绿素含量、叶片绿色的浓度、生物量的产生以及硝酸盐和磷酸盐去除方面表现出了差异。一般而言，干生物量与硝酸盐和磷酸盐的去除程度相关（r = 0.339~0.501）。本地树种的根、叶和总干生物量显示出与硝酸盐去除程度之间的中等至强相关性（r 分别为0.811、0.657和0.727）。速生植物的叶片干生物量与两种污染物的去除程度也显示出中等至强相关性（r 分别为0.707和0.609）。低生长植株的根系生物量与磷的去除有很强的相关性（r = 0.707），但与硝酸盐去除的相关性较弱（r = 0.557）。这些结果对于选择用于生物滞留系统的植物是有价值的。

关键词： 氮     磷     植物性状     生物保留系统     雨水     热带植物     富营养污染物     本土植物    

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The investigation of fly ash based asphalt binders using atomic force microscope

Rajan SAHA, Kyle MALLOY, Emil BAUTISTA, Konstantin SOBOLEV

《结构与土木工程前沿（英文）》 2017年 第11卷 第4期   页码 380-387 doi: 10.1007/s11709-017-0437-3

摘要： Atomic Force Microscope (AFM) is a relatively new technique for investigation of construction materials. In this study AFM was used to investigate the interaction of asphalt binder with fly ash. Fly ash is a coal combustion byproduct of electric power utilities having pozzolanic properties and commonly used in Portland cement concrete. In this study, an investigation was made by using different types of fly ash with two types of asphalt binders such as PG 58-28 and PG 64-28. Asphalt microstructure is divided into four subgroups such as Saturates, Aromatics, Resins and Asphaltenes (SARA). These four phases can be distinguished by the atomic force microscope. The interaction of these phases affected by introducing fly-ash was investigated and correlation with rheological properties was observed.

关键词： AFM     fly ash     bee     rheology     asphalt    

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Hybrid optimization algorithm for modeling and management of micro grid connected system

Kallol ROY,Kamal Krishna MANDAL

《能源前沿（英文）》 2014年 第8卷 第3期   页码 305-314 doi: 10.1007/s11708-014-0308-8

摘要： In this paper, a hybrid optimization algorithm is proposed for modeling and managing the micro grid (MG) system. The management of distributed energy sources with MG is a multi-objective problem which consists of wind turbine (WT), photovoltaic (PV) array, fuel cell (FC), micro turbine (MT) and diesel generator (DG). Because, perfect economic model of energy source of the MG units are needed to describe the operating cost of the output power generated, the objective of the hybrid model is to minimize the fuel cost of the MG sources such as FC, MT and DG. The problem formulation takes into consideration the optimal configuration of the MG at a minimum fuel cost, operation and maintenance costs as well as emissions reduction. Here, the hybrid algorithm is obtained as artificial bee colony (ABC) algorithm, which is used in two stages. The first stage of the ABC gets the optimal MG configuration at a minimum fuel cost for the required load demand. From the minimized fuel cost functions, the operation and maintenance cost as well as the emission is reduced using the second stage of the ABC. The proposed method is implemented in the Matlab/Simulink platform and its effectiveness is analyzed by comparing with existing techniques. The comparison demonstrates the superiority of the proposed approach and confirms its potential to solve the problem.

关键词： micro grid (MG)     multi-objective function     artificial bee colony (ABC)     fuel cost     operation and maintenance cost    

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改进的二进制人工蜂群算法 Research Articles

Rafet DURGUT

《信息与电子工程前沿（英文）》 2021年 第22卷 第8期   页码 1080-1091 doi: 10.1631/FITEE.2000239

摘要： 人工蜂群算法是一种基于群体智能并受蜜蜂觅食行为启发的演变优化算法。由于人工蜂群算法已被开发用于搜索连续的搜索空间来获得最优解，因此需要对其进行修改以应用于二进制优化问题。本文修改了人工蜂群算法来解决二进制优化问题，并将其命名为改进的二进制人工蜂群算法。提出的方法包括基于适应值和不同决策变量选择的更新机制。因此，我们的目标是通过增加探索能力来防止人工蜂群算法陷入局部最小值。将改进的二进制人工蜂群算法与人工蜂群算法的3种变体和其他文献中的启发式算法进行了比较，并使用了大家熟知的OR-Library数据集，其中包含为无容量限制的设施选址位置问题准备的15个问题实例。计算结果表明，该算法在收敛速度和鲁棒性方面均优于其他算法。可通过https://github.com/rafetdurgut/ibinABC获取算法源码。

关键词： 人工蜂群；二进制优化；无容量限制的设施选址位置问题（UFLP）    

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Novel hybrid models of ANFIS and metaheuristic optimizations (SCE and ABC) for prediction of compressive strength of concrete using rebound hammer field test

Dung Quang VU; Fazal E. JALAL; Mudassir IQBAL; Dam Duc NGUYEN; Duong Kien TRONG; Indra PRAKASH; Binh Thai PHAM

《结构与土木工程前沿（英文）》 2022年 第16卷 第8期   页码 1003-1016 doi: 10.1007/s11709-022-0846-9

摘要： In this study, we developed novel hybrid models namely Adaptive Neuro Fuzzy Inference System (ANFIS) optimized by Shuffled Complex Evolution (SCE) on the one hand and ANFIS with Artificial Bee Colony (ABC) on the other hand. These were used to predict compressive strength (Cs) of concrete relating to thirteen concrete-strength affecting parameters which are easy to determine in the laboratory. Field and laboratory tests data of 108 structural elements of 18 concrete bridges of the Ha Long-Van Don Expressway, Vietnam were considered. The dataset was randomly divided into a 70:30 ratio, for training (70%) and testing (30%) of the hybrid models. Performance of the developed fuzzy metaheuristic models was evaluated using standard statistical metrics: Correlation Coefficient (R), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results showed that both of the novel models depict close agreement between experimental and predicted results. However, the ANFIS-ABC model reflected better convergence of the results and better performance compared to that of ANFIS-SCE in the prediction of the concrete Cs. Thus, the ANFIS-ABC model can be used for the quick and accurate estimation of compressive strength of concrete based on easily determined parameters for the design of civil engineering structures including bridges.

关键词： shuffled complex evolution     artificial bee colony     ANFIS     concrete     compressive strength     Vietnam    

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标题 作者 时间 类型 操作

consideration of uncertainties for deployment of distributed energy resources using interactive honey bee

Iraj AHMADIAN,Oveis ABEDINIA,Noradin GHADIMI

期刊论文

Artificial bee colony optimization for economic dispatch with valve point effect

Yacine LABBI,Djilani Ben ATTOUS,Belkacem MAHDAD

期刊论文

An improved artificial bee colony algorithm with MaxTF heuristic rule for two-sided assembly line balancing

Xiaokun DUAN, Bo WU, Youmin HU, Jie LIU, Jing XIONG

期刊论文

Damage assessment and diagnosis of hydraulic concrete structures using optimization-based machine learning technology

期刊论文

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

期刊论文

面向热带地区植物修复的植物性状研究

Xiangting Cleo Chen, Liling Huang, Tze Hsien Agnes Chang, Bee Lian Ong, Say Leong Ong, Jiangyong Hu

期刊论文

The investigation of fly ash based asphalt binders using atomic force microscope

Rajan SAHA, Kyle MALLOY, Emil BAUTISTA, Konstantin SOBOLEV

期刊论文

Hybrid optimization algorithm for modeling and management of micro grid connected system

Kallol ROY,Kamal Krishna MANDAL

期刊论文

改进的二进制人工蜂群算法

Rafet DURGUT

期刊论文

Novel hybrid models of ANFIS and metaheuristic optimizations (SCE and ABC) for prediction of compressive strength of concrete using rebound hammer field test

Dung Quang VU; Fazal E. JALAL; Mudassir IQBAL; Dam Duc NGUYEN; Duong Kien TRONG; Indra PRAKASH; Binh Thai PHAM

期刊论文