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Complex ontology alignment for autonomous systems via the Compact Co-Evolutionary Brain Storma* optimization algorithm

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ISA TRANSACTIONS 2023年 132卷 190-198页

作者： Xue, Xingsi Fujian Univ Technol Fujian Prov Key Lab Big Data Min & Applicat Fuzhou 350118 Fujian Peoples R China Fujian Univ Technol Intelligent Informat Proc Res Ctr Fuzhou 350118 Fujian Peoples R China

Autonomous Systems (ASs) that work in the open, dynamic environment are required to share their data entities and semantics to implement the co-operations. Typically, AS's data schemas and semantics are described via ontology. Since ASs need to maintain their autonomy and conceptual specificity, their ontologies might define one concept with different terms or in different contexts, which yields the heterogeneity issue and hampers their co-operations. An effective solution is to establish a set of data entity's correspondences through the Ontology Alignment (OA). Sine the simple correspondence of one-to-one style lacks expressiveness and cannot completely cover different types of heterogeneity, ASs' co-operations require using the complex correspondence of one-to-many or many-to-may style. Inspired by the success of applying the Brain Storma* optimization algorithm (BSO) to solve diverse complex optimization problems, this work proposes a Compact Co-Evolutionary BSO (CCBSO) to face the challenge of aligning AS ontologies. In particular, the AS ontology aligning problem is formally defined, a hybrid confidence measure for distinguishing the simple and complex correspondences is proposed, and a problem-specific CCBSO is presented. The experiment tests CCBSO's performance on different AS ontology aligning tasks, which consist of two simple ontology aligning tasks and one complex ontology aligning track. The experimental results show that CCBSO outperforms the state-of-the-art ontology aligning techniques on all simple and complex ontology aligning tasks.(c) 2022 ISA. Published by Elsevier Ltd. All rights reserved.

关键词： Autonomous system Complex ontology alignment Compact Co-Evolutionary Brain Storm optimization algorithm Hybrid confidence measure

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A novela* optimization algorithm for assemblable region boundary points search in high-dimensional posture space of parts assembly

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INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY 2023年第9-10期128卷 4615-4633页

作者： Li, Yue Qie, Yifan Huang, Zhicheng Qiao, Lihong Anwer, Nabil Beihang Univ Sch Mech Engn & Automat Beijing 100191 Peoples R China Univ Paris Saclay ENS Paris Saclay LURPA F-91190 Gif Sur Yvette France

Surface deviations caused by manufacturing errors have an essential influence on the assemblability of mechanical parts. The concept of assemblable region in the posture space has been introduced as an effective tool to express the posture feasible adjustment range of non-ideal parts in the assembly process. It can reflect the complexity of posture control through ergonomic principles and thus indicates the difficulty and feasibility of assembly. The assemblability considering surface deviations can be evaluated based on the geometric and topological (G & T) properties of the assemblable region. However, one necessary precondition for realizing the analysis of G & T properties is to obtain the boundary of assemblable region in high-dimensional posture space while guaranteeing the computational efficiency. In this paper, a novela* optimization algorithm is proposed for the boundary calculation of the assemblable region. The high-dimensional irregular boundary calculation problem is firstly transformed into a boundary points search problem. Then, a new heuristic boundary points diffusion search (BDS) algorithm is developed. Two main parts are designed within the proposed algorithm, including the diffusion search rules as well as the collaborative search process. By optimizing the location and quantity of points in searching group, the algorithm can efficiently achieve the boundary points search goal and realize the boundary calculation of assemblable region. Finally, two typical cases are carried out to verify the feasibility of the proposed algorithm. The comparison with an improved genetic algorithm in application also highlights the efficiency and stability of the proposed algorithm.

关键词： Assemblability evaluation Posture space Assemblable region Boundary points search optimization algorithm

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A slave ants based ant colonya* optimization algorithm for task scheduling in cloud computing environments

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HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES 2017年第1期7卷 1页

作者： Moon, YoungJu Yu, HeonChang Gil, Joon-Min Lim, JongBeom Korea Univ Dept Comp Sci & Engn Seoul South Korea Catholic Univ Daegu Sch Informat Technol Engn Gyeongbuk South Korea Korea Polytech Univ Dept Game & Multimedia Engn Shihung Gyeonggi Do South Korea

Since cloud computing provides computing resources on a pay per use basis, a task scheduling algorithm directly affects the cost for users. In this paper, we propose a novel cloud task scheduling algorithm based on ant colony optimization that allocates tasks of cloud users to virtual machines in cloud computing environments in an efficient manner. To enhance the performance of the task scheduler in cloud computing environments with ant colony optimization, we adapt diversification and reinforcement strategies with slave ants. The proposed algorithm solves the global optimization problem with slave ants by avoiding long paths whose pheromones are wrongly accumulated by leading ants.

关键词： Task scheduling Ant colony system optimization algorithm Cloud computing

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Development of a WWTP influent characterization method for an activated sludge model using ana* optimization algorithm

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MEMBRANE WATER TREATMENT 2018年第3期9卷 155-162页

作者： You, Kwangtae Kim, Jongrack Pak, Gijung Yun, Zuwhan Kim, Hyunook UnU Inc Seoul 08390 South Korea Korea Univ Dept Environm Engn Sejong 30019 South Korea Univ Seoul Dept Energy & Environm Syst Engn Seoul 02504 South Korea

Process modeling with activated sludge models (ASMs) is useful for the design and operational improvement of biological nutrient removal (BNR) processes. Effective utilization of ASMs requires the influent fraction analysis (IFA) of the wastewater treatment plant (WWTP). However, this is difficult due to the time and cost involved in the design and operation steps, thereby declining the simulation reliability. Harmony Search (HS) algorithm was utilized herein to determine the relationships between composite variables and state variables of the model IWA ASM1. Influent fraction analysis was used in estimating fractions of the state variables of the WWTP influent and its application to 9 wastewater treatment processes in South Korea. The results of influent Ss and Xs+X-BH, which are the most sensitive variables for design of activated sludge process, are estimated within the error ranges of 8.9-14.2% and 3.8-6.4%, respectively. Utilizing the chemical oxygen demand (COD) fraction analysis for influent wastewater, it was possible to predict the concentrations of treated organic matter and nitrogen in 9 full scale BNR processes with high accuracy. In addition, the results of daily influent fraction analysis (D-IFA) method were superior to those of the constant influent fraction analysis (C-IFA) method.

关键词： ASMs COD influent fraction analyzer (IFA) Harmony Search (HS) optimization algorithm WWTPs

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Image segmentation based on equivalent three-dimensional entropy method and artificial fish swarma* optimization algorithm

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OPTICAL ENGINEERING 2018年第10期57卷 1-7页

作者： Lei, Xiangxiao Ouyang, Honglin Xu, Lijuan Hunan Univ Coll Elect & Informat Engn Changsha Hunan Peoples R China Changsha Social Work Coll Sch Elect Informat Engn Changsha Hunan Peoples R China

To improve the timeliness of the three-dimensional (3-D) maximum entropy method, an image segmentation method based on equivalent 3-D entropy and artificial fish swarma* optimization algorithm is proposed. An equivalent 3-D entropy method without logarithmic operation is developed, and its equivalence is proved theoretically. The optimal threshold is determined based on the artificial fish swarma* optimization algorithm so as to avoid exhaustive search and improve algorithm efficiency. The experimental results demonstrate that the proposed method is more time-efficient than the traditional 3-D entropy method and the equivalent 3-D entropy method without affecting segmentation. Compared with the one-dimensional entropy method and the two-dimensional entropy method, it is obviously superior in noise immunity and detail preservation. (C) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)

关键词： image segmentation maximum entropy three-dimensional histogram optimization algorithm artificial fish-swarm algorithm

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A newa* optimization algorithm for the design of aperiodic multilayer mirror for 17.1 nm and 30.4 nm

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OPTOELECTRONICS AND ADVANCED MATERIALS-RAPID COMMUNICATIONS 2013年第3-4期7卷 167-172页

作者： Zhu, Huaxin Gao, Jinsong Wang, Tongtong Zhao, Jingli Liu, Guilin Li, Shuai Jiangnan Univ Sch Sci Wuxi 214122 Jiangsu Peoples R China Chinese Acad Sci Changchun Inst Opt Fine Mech & Phys Key Lab Opt Syst Adv Mfg Technol Changchun 130033 Peoples R China

A new algorithm, Genetic/Tabu hybrid algorithm (GTHA) to optimize the aperiodic multilayer mirrors which combines the advantages of genetic algorithm (GAs) with tabu search (TS) algorithm is proposed in the extreme ultraviolet (EUV) range. Aperiodic multilayers are designed using GTHA for the selection of Fe-IX and He-II emission lines contrasting to the traditional periodic multilayers for a single wavelength. Materials of Mo and Si are selected for their high stability and fairly high reflectivity. High reflectance of 48.62% for the Fe-IX line (lambda=17.1nm) and reflectance of 20.57% for the He-II line (lambda=30.4nm) are reached by the new algorithm. Comparisons between aperiodic multilayers found by GTHA and the ones optimized using GAs indicate the effectiveness and reliability of the new hybrid algorithm. The aperiodic designs are compared with the periodic ones as well. And the aperiodic multilayers found by GTHA also have the better performance than periodic ones. The practicability of the aperiodic design optimized by GHTA is verified by the sensitivity analyses to thicknesses errors, which indicated it more feasible to fabricate the aperiodic multilayers in practice.

关键词： Optical thin Elm optimization algorithm Aperiodic multilayers

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optimization of Self-Learning in Computer Engineering Courses: An Intelligent Software System Supported by Artificial Neural Network and Vortexa* optimization algorithm

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COMPUTER APPLICATIONS IN ENGINEERING EDUCATION 2017年第1期25卷 142-156页

作者： Kose, Utku Arslan, Ahmet Usak Univ Comp Sci Applicat & Res Ctr Usak Turkey Konya Food & Agr Univ Dept Comp Engn Konya Turkey

Self-learning process is an important factor that enables learners to improve their own educational experiences when they are away of face-to-face interactions with the teacher. A well-designed self-learning activity process supports both learners and teachers to achieve educational objectives rapidly. Because of this, there has always been a remarkable trend on developing alternative self-learning approaches. In this context, this study is based on two essential objectives. Firstly, it aims to introduce an intelligent software system, which optimizes and improves computer engineering students' self-learning processes. Secondly, it aims to improve computer engineering students' self-learning during the courses. As general, the software system introduced here evaluates students' intelligence levels according to the Theory of Multiple Intelligences and supports their learning via accurately chosen materials provided over the software interface. The evaluation mechanism of the system is based on a hybrid Artificial Intelligence approach formed by an Artificial Neural Network, and ana* optimization algorithm called as Vortexa* optimization algorithm (VOA). The system is usable for especially technical courses taught at computer engineering departments of universities and makes it easier to teach abstract subjects. For having idea about success of the system, it has been tested with students and positive results on optimizing and improving self-learning have been obtained. Additionally, also a technical evaluation has been done previously, in order to see if the VOA is a good choice to be used in the system. It can be said that the whole obtained results encourage the authors to continue to future works. (C) 2017 Wiley Periodicals, Inc.

关键词： self-learning theory of multiple intelligences artificial neural networks vortex optimization algorithm computer engineering

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Jaya* optimization algorithm for transient response and stability enhancement of a fractional-order PID based automatic voltage regulator system

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ALEXANDRIA ENGINEERING JOURNAL 2020年第4期59卷 2429-2440页

作者： Jumani, Touqeer Ahmed Mustafa, Mohd Wazir Hussain, Zohaib Rasid, Madihah Md Saeed, Muhammad Salman Memon, Mehran M. Khan, Ilyas Nisar, Kottakkaran Sooppy Univ Teknol Malaysia Sch Elect Engn Skudai Johor Bahru Malaysia Mehran Univ Engn & Technol Dept Elect Engn SZAB Campus Khairpur Mirs Pakistan Mehran Univ Engn & Technol Dept Elect Engn Jamshoro Pakistan Multan Elect Power Co Multan Pakistan Ton Duc Thang Univ Fac Math & Stat Ho Chi Minh City 72915 Vietnam Prince Sattam bin Abdulaziz Univ Coll Arts & Sci Dept Math Wadi Aldawaser 11991 Saudi Arabia

Considering the higher flexibility in tuning process and finer control action of the fractional-order proportional integral derivative (FOPID) controller over the conventional propor-tional integral derivative (PID) controller, this paper explores its application in the automatic volt-age regulator system. FOPID contains five tuning parameters as compared to three in the conventional PID controller. The additional tuning knobs in FOPID provide increased control flex-ibility and precise control action, however, their inclusion makes the tuning process more complex and tedious. Thus, the intelligence of an artificial intelligence (AI) technique called jaya optimiza-tion algorithm (JOA) is utilized in order to obtain an optimal combination of FOPID gains which further led to the optimal transient response and improved stability of the considered AVR system. To validate the performance superiority of the proposed approach its corresponding system's dynamic response is compared with that of the other well-known AI-based approaches explored in recent literature. Furthermore, the stability study of the proposed AVR system is carried out by evaluating its pole/zero and bode maps. Finally, the robustness of the proposed optimized AVR system against the system's parameter variation is evaluated by varying the time constants of all the four components of AVR (generator, exciter, amplifier and sensor) from-50% to +50% independently. The proposed algorithm based FOPID tuning technique provides 59.82%, 56.09%, 14.94%, 34.24%, 35.70%, 21.64%, 12.0%, 41.33%, 14.84% and 15.17% reduced over-shoot than that of differential evolution (DE), particle swarm optimization (PSO), Artificial Bee Colony (ABC), Bibliography Based optimization (BBO), Grasshoppera* optimization algorithm (GOA), Pattern Search algorithm (PSA), Improved Kidney Inspired algorithm (IKA), Whalea* optimization algorithm (WOA), Salp Swarm algorithm (SSA) and Local Unimodal Sampling (LUS) algorithm respectively, thus validat

关键词： optimization algorithm Transient response FOPID AVR JOA

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Pairing-Free Identity-Based Digital Signature algorithm for Broadcast Authentication Based on Modified ECC Using Battle Royala* optimization algorithm

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WIRELESS PERSONAL COMMUNICATIONS 2022年第3期123卷 2341-2365页

作者： Kumar, Vivek Ray, Sangram Natl Inst Technol Sikkim Dept Comp Sci & Engn Sikkim 737139 India

In wireless sensor networks (WSN), broadcast authentication is an important security service that provides secure communication. Several mobile users are allowed by this broadcast authentication service. There are some concerns in the sensor network, which depend on security based on maintaining consumer untracking and privacy for data transmission. To overcome the concern of security issues, an Identity (ID)-based cryptography method is introduced. This paper presented a Pairing-Free Identity-based Digital Signature (PF-IBDS) algorithm based on Modified Elliptic Curve Cryptography (MECC) by using Battle Royala* optimization algorithm. The main aim of this paper is to secure the data transmission for message authentication. The proposed protocol is to enhance the speed of authentication, reduce the signature size and speed up the signature verification. Moreover, this paper analyses the security by BAN (Burrows-Abadi-Needham) logic and comparing with the existing protocols. It is verified that the developed protocol is protected and well-organized for peer-to-peer communications. Therefore, the proposed method offers secure key management, fast authentication, and also minimizes the computation overhead. The proposed authentication process is simulated in the Java platform. The performance of this protocol has compared with other existing approaches in terms of key verification time, key generation time and computational time.

关键词： Key generation Authentication WSN optimization algorithm Security Elliptic curve cryptography Identity-based signature Pairing-free

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Go-Caterpillar Mutation and Itsa* optimization algorithm for Synthesis of Large-Scale Sparse Planar Arrays

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IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION 2023年第3期71卷 2194-2207页

作者： Zhao, Heng Ban, Yong-Ling Liu, Yanhui Hu, Jun Nie, Zaiping Univ Elect Sci & Technol China Sch Elect Sci & Engn Chengdu 611731 Peoples R China

Optimizing the layout of sparse planar arrays constrained by minimum element spacing to reduce the peak sidelobe level (PSLL) is a difficult and challenging task in engineering applications. Here, a new sparse array design method is proposed under the constraints of aperture size, the number of array elements, and minimum spacing between elements. The approach is based on a new element mutation method which is proposed for mutating the position of any element within the aperture without changing the position of other elements. Because a mutating element can be thought of as being placed inside the board like a black/white stone in go or crawling somewhere nearby like a caterpillar, we call it go-caterpillar-mutation (GCM). Based on GCM, a stochastica* optimization algorithm (GCM-OA) is proposed to optimize the layout of sparse planar arrays. Several examples demonstrate the robustness and rapidity of GCM-OA in reducing PSLL by adjusting the array element positions under various constraints.

关键词： Finite element analysis Apertures Planar arrays Layout Stochastic processes Encoding Antenna radiation patterns Antenna array go-caterpillar-mutation (GCM) optimization algorithm position perturbation model (PPM) sparse planar array

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