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Optimization of thread partitioning parameters in speculative multithreading based on artificial immunealgorithm

Yu-xiang LI,Yin-liang ZHAO,Bin LIU,Shuo JI

《信息与电子工程前沿（英文）》 2015年 第16卷 第3期   页码 205-216 doi: 10.1631/FITEE.1400172

摘要： Thread partition plays an important role in speculative multithreading (SpMT) for automatic parallelization of irregular programs. Using unified values of partition parameters to partition different applications leads to the fact that every application cannot own its optimal partition scheme. In this paper, five parameters affecting thread partition are extracted from heuristic rules. They are the dependence threshold (DT), lower limit of thread size (TSL), upper limit of thread size (TSU), lower limit of spawning distance (SDL), and upper limit of spawning distance (SDU). Their ranges are determined in accordance with heuristic rules, and their step-sizes are set empirically. Under the condition of setting speedup as an objective function, all combinations of five threshold values form the solution space, and our aim is to search for the best combination to obtain the best thread granularity, thread dependence, and spawning distance, so that every application has its best partition scheme. The issue can be attributed to a single objective optimization problem. We use the artificial immune algorithm (AIA) to search for the optimal solution. On Prophet, which is a generic SpMT processor to evaluate the performance of multithreaded programs, Olden benchmarks are used to implement the process. Experiments show that we can obtain the optimal parameter values for every benchmark, and Olden benchmarks partitioned with the optimized parameter values deliver a performance improvement of 3.00% on a 4-core platform compared with a machine learning based approach, and 8.92% compared with a heuristics-based approach.

关键词： Speculative multithreading     Thread partitioning     Artificial immune algorithm    

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基于势场导向权的改进机器人路径规划免疫算法

王孙安,吴灿阳

《中国工程科学》 2013年 第15卷 第1期   页码 73-78

摘要：

为了解决复杂环境中移动机器人的路径规划问题，结合人工势场法计算量小的特性和人工免疫网络的自适应调节能力，提出了一种改进的路径规划免疫算法。为了提高免疫网络的搜索能力以及免疫网络的收敛性，将人工势场法的规划结果作为先验知识构建了导向权，同时将抗体命令清晰度和抗体转移后的距离变化作为变量，构建了新的抗体转移概率算子。仿真结果表明，与其他算法相比，新算法在最优规划能力和网络收敛性能方面都有明显提高。

关键词： 免疫网络     人工势场     移动机器人     路径规划    

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Application of a Novel Fuzzy Clustering Method Based on Chaos Immune Evolutionary Algorithm for Edge

《机械工程前沿（英文）》 2006年 第1卷 第1期   页码 85-89 doi: 10.1007/s11465-005-0023-6

摘要：

A novel fuzzy clustering method based on chaos immune evolutionary algorithm (CIEFCM) is presented to solve fuzzy edge detection problems in image processing. In CIEFCM, a tiny disturbance is added to a filial generation group using a chaos variable and the disturbance amplitude is adjusted step by step, which greatly improves the colony diversity of the immune evolution algorithm (IEA). The experimental results show that the method not only can correctly detect the fuzzy edge and exiguous edge but can evidently improve the searching efficiency of fuzzy clustering algorithm based on IEA.

关键词： disturbance amplitude     disturbance     diversity     generation     processing    

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Interaction behavior and load sharing pattern of piled raft using nonlinear regression and LM algorithm-basedartificial neural network

《结构与土木工程前沿（英文）》 2021年 第15卷 第5期   页码 1181-1198 doi: 10.1007/s11709-021-0744-6

摘要： In the recent era, piled raft foundation (PRF) has been considered an emergent technology for offshore and onshore structures. In previous studies, there is a lack of illustration regarding the load sharing and interaction behavior which are considered the main intents in the present study. Finite element (FE) models are prepared with various design variables in a double-layer soil system, and the load sharing and interaction factors of piled rafts are estimated. The obtained results are then checked statistically with nonlinear multiple regression (NMR) and artificial neural network (ANN) modeling, and some prediction models are proposed. ANN models are prepared with Levenberg–Marquardt (LM) algorithm for load sharing and interaction factors through backpropagation technique. The factor of safety (FS) of PRF is also estimated using the proposed NMR and ANN models, which can be used for developing the design strategy of PRF.

关键词： interaction     load sharing ratio     piled raft     nonlinear regression     artificial neural network    

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基于人工免疫算法的SVG电压外环控制器控制策略

杨建宁,孙玉坤,李自成,孙运全

《中国工程科学》 2007年 第9卷 第10期   页码 30-35

摘要：

针对高维非线性电力系统复杂的控制对象，在静止无功发生器（SVG）的电压偏差-无功的控制方法上，采用人体免疫系统维持自身功能正常的机理，以稳定电力系统工作状态,提出基于人工免疫算法的SVG外环控制器控制策略。研究中识别电力系统中相应抗原物质的电压变动因素，细胞激活生成过程的模糊建模，运用Mamdani模糊推理和重心中心解模糊方法，得到内环控制所需要的无功参考值指令。通过单机双闭环控制的SVG控制器离线仿真，对三相对称短路故障后控制的影响分析，并与PI控制方式比较。结果表明，所提出的仿生免疫机理的控制方案对于SVG中动态无功调节过程和对电力系统稳定性的控制作用是有效的。

关键词： 电力系统     静止无功发生器     类人体免疫反应模型     李雅普诺夫能量函数    

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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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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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免疫进化机制及其在时序模式挖掘中的应用研究

杨炳儒,秦奕青,宋泽锋

《中国工程科学》 2008年 第10卷 第4期   页码 84-89

摘要：

针对目前动态数据挖掘中存在的问题，提出基于数据增量的动态挖掘进程概念；在动态挖掘进程和生物免疫进化过程的相似性基础上，提出了知识发现中的免疫进化机制的基本内涵；给出了基于免疫进化机制的时序模式挖掘算法及其实验分析，以验证理论的正确性和有效性。

关键词： 动态数据挖掘     免疫算法     动态挖掘进程     免疫进化机制     时序模式挖掘    

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Vibration-based crack prediction on a beam model using hybrid butterfly optimization algorithm with artificial

Abdelwahhab KHATIR; Roberto CAPOZUCCA; Samir KHATIR; Erica MAGAGNINI

《结构与土木工程前沿（英文）》 2022年 第16卷 第8期   页码 976-989 doi: 10.1007/s11709-022-0840-2

摘要： Vibration-based damage detection methods have become widely used because of their advantages over traditional methods. This paper presents a new approach to identify the crack depth in steel beam structures based on vibration analysis using the Finite Element Method (FEM) and Artificial Neural Network (ANN) combined with Butterfly Optimization Algorithm (BOA). ANN is quite successful in such identification issues, but it has some limitations, such as reduction of error after system training is complete, which means the output does not provide optimal results. This paper improves ANN training after introducing BOA as a hybrid model (BOA-ANN). Natural frequencies are used as input parameters and crack depth as output. The data are collected from improved FEM using simulation tools (ABAQUS) based on different crack depths and locations as the first stage. Next, data are collected from experimental analysis of cracked beams based on different crack depths and locations to test the reliability of the presented technique. The proposed approach, compared to other methods, can predict crack depth with improved accuracy.

关键词： damage prediction     ANN     BOA     FEM     experimental modal analysis    

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Real-time immune-inspired optimum state-of-charge trajectory estimation using upcoming route information

Ahmad MOZAFFARI,Mahyar VAJEDI,Nasser L. AZAD

《机械工程前沿（英文）》 2015年 第10卷 第2期   页码 154-167 doi: 10.1007/s11465-015-0336-z

摘要：

The main proposition of the current investigation is to develop a computational intelligence-based framework which can be used for the real-time estimation of optimum battery state-of-charge (SOC) trajectory in plug-in hybrid electric vehicles (PHEVs). The estimated SOC trajectory can be then employed for an intelligent power management to significantly improve the fuel economy of the vehicle. The devised intelligent SOC trajectory builder takes advantage of the upcoming route information preview to achieve the lowest possible total cost of electricity and fossil fuel. To reduce the complexity of real-time optimization, the authors propose an immune system-based clustering approach which allows categorizing the route information into a predefined number of segments. The intelligent real-time optimizer is also inspired on the basis of interactions in biological immune systems, and is called artificial immune algorithm (AIA). The objective function of the optimizer is derived from a computationally efficient artificial neural network (ANN) which is trained by a database obtained from a high-fidelity model of the vehicle built in the Autonomie software. The simulation results demonstrate that the integration of immune inspired clustering tool, AIA and ANN, will result in a powerful framework which can generate a near global optimum SOC trajectory for the baseline vehicle, that is, the Toyota Prius PHEV. The outcomes of the current investigation prove that by taking advantage of intelligent approaches, it is possible to design a computationally efficient and powerful SOC trajectory builder for the intelligent power management of PHEVs.

关键词： trip information preview     intelligent transportation     state-of-charge trajectory builder     immune systems     artificial neural network    

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Advances on immune-related adverse events associated with immune checkpoint inhibitors

Yong Fan, Yan Geng, Lin Shen, Zhuoli Zhang

《医学前沿（英文）》 2021年 第15卷 第1期   页码 33-42 doi: 10.1007/s11684-019-0735-3

摘要： Immunotherapy has recently led to a paradigm shift in cancer therapy, in which immune checkpoint inhibitors (ICIs) are the most successful agents approved for multiple advanced malignancies. However, given the nature of the non-specific activation of effector T cells, ICIs are remarkably associated with a substantial risk of immune-related adverse events (irAEs) in almost all organs or systems. Up to 90% of patients who received ICIs combination therapy experienced irAEs, of which majority were low-grade toxicity. Cytotoxic lymphocyte antigen-4 and programmed cell death protein-1/programmed cell death ligand 1 inhibitors usually display distinct features of irAEs. In this review, the mechanisms of action of ICIs and how they may cause irAEs are described. Some unsolved challenges, however really engrossing issues, such as the association between irAEs and cancer treatment response, tumor response to irAEs therapy, and ICIs in challenging populations, are comprehensively summarized.

关键词： cancer     immunotherapy     immune checkpoint inhibitors     immune-related adverse events     review    

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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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Natural killer cells in liver diseases

null

《医学前沿（英文）》 2018年 第12卷 第3期   页码 269-279 doi: 10.1007/s11684-018-0621-4

摘要：

The liver has been characterized as a frontline lymphoid organ with complex immunological features such as liver immunity and liver tolerance. Liver tolerance plays an important role in liver diseases including acute inflammation, chronic infection, autoimmune disease, and tumors. The liver contains a large proportion of natural killer (NK) cells, which exhibit heterogeneity in phenotypic and functional characteristics. NK cell activation, well known for its role in the immune surveillance against tumor and pathogen-infected cells, depends on the balance between numerous activating and inhibitory signals. In addition to the innate direct “killer” functions, NK cell activity contributes to regulate innate and adaptive immunity (helper or regulator). Under the setting of liver diseases, NK cells are of great importance for stimulating or inhibiting immune responses, leading to either immune activation or immune tolerance. Here, we focus on the relationship between NK cell biology, such as their phenotypic features and functional diversity, and liver diseases.

关键词： natural killer cell     phenotype     immune activation     immune tolerance     liver diseases    

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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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Persistence of humoral and cellular immune response after SARS-CoV-2 infection: opportunities and challenges

Tangchun Wu

《医学前沿（英文）》 2020年 第14卷 第6期   页码 816-819 doi: 10.1007/s11684-020-0823-4

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标题 作者 时间 类型 操作

Optimization of thread partitioning parameters in speculative multithreading based on artificial immunealgorithm

Yu-xiang LI,Yin-liang ZHAO,Bin LIU,Shuo JI

期刊论文

基于势场导向权的改进机器人路径规划免疫算法

王孙安,吴灿阳

期刊论文

Application of a Novel Fuzzy Clustering Method Based on Chaos Immune Evolutionary Algorithm for Edge

期刊论文

Interaction behavior and load sharing pattern of piled raft using nonlinear regression and LM algorithm-basedartificial neural network

期刊论文

基于人工免疫算法的SVG电压外环控制器控制策略

杨建宁,孙玉坤,李自成,孙运全

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

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

免疫进化机制及其在时序模式挖掘中的应用研究

杨炳儒,秦奕青,宋泽锋

期刊论文

Vibration-based crack prediction on a beam model using hybrid butterfly optimization algorithm with artificial

Abdelwahhab KHATIR; Roberto CAPOZUCCA; Samir KHATIR; Erica MAGAGNINI

期刊论文

Real-time immune-inspired optimum state-of-charge trajectory estimation using upcoming route information

Ahmad MOZAFFARI,Mahyar VAJEDI,Nasser L. AZAD

期刊论文

Advances on immune-related adverse events associated with immune checkpoint inhibitors

Yong Fan, Yan Geng, Lin Shen, Zhuoli Zhang

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

Natural killer cells in liver diseases

null

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

Persistence of humoral and cellular immune response after SARS-CoV-2 infection: opportunities and challenges

Tangchun Wu

期刊论文