检索结果-内蒙古大学图书馆

arithmetic optimization algorithm with cosine composite chaotic mapping in polar coordinate system for economic load dispatching problems in power systems

引用

APPLIED SOFT COMPUTING 2025年 175卷

作者： Li, Yi-Xuan Wang, Jie-Sheng Zhang, Si-Wen Zhang, Shi-Hui Guan, Xin-Yi Ma, Xin-Ru Univ Sci & Technol Liaoning Sch Elect & Informat Engn Anshan Liaoning Peoples R China

Economic load dispatch (ELD) aims to minimize the total cost of generating electricity while satisfying load demand and different operational constraints. The arithmetic optimization algorithm (AOA) with cosine composite chaotic mapping in polar coordinate system is put forward to solve the ELD problems in the power system with the valve point effect, prohibited operation area, transmission loss and other factors. Firstly, seven polar coordinate system chaotic mappings are proposed to be embedded into the MOP and MOA parameters in the AOA. Secondly, a chaotic system based on the cosine transform is put forward. Then, the proposed cosine transform based chaotic system is combined with polar coordinate system chaotic mapping to form polar coordinate system cosine transform composite chaotic mapping. Eventually, these six polar coordinate system cosine transform composite chaotic mapping is then embedded into the MOA and MOP of the AOA to balance the algorithm's global and local search capabilities, improve the performance of the algorithm and avoid falling into the local optima. The superiority of the improved algorithm is verified by employing 12 benchmark test functions in CEC2022. Then, it is compared with the Coati optimization algorithm (COA), Prairie Dog optimization (PDO), Butterfly optimization algorithm (BOA), Reptile Search algorithm (RSA), Bat algorithm (BAT) and Osprey optimization algorithm (OOA) to verify its convergence. The ELD problem for a total demand of 2500 MW is solved by using the AOA with cosine composite chaotic mapping in polar coordinate system. The experimental results show that the improved AOA outperforms other optimization algorithms on the 12 benchmark functions in CEC2022 and the ELD problems.

关键词： Economic load dispatching arithmetic optimization algorithm Two-dimensional Chaotic mapping Cosine composite chaotic system Valve point effect

来源：评论

学校读者我要写书评

暂无评论

arithmetic optimization algorithm with three-dimensional chaotic mapping in spherical coordinate system for combined economic emission dispatch problem

引用

APPLIED ENERGY 2025年 380卷

作者： Li, Yi-Xuan Wang, Jie-Sheng Guan, Xin-Yi Wang, Xiao-Tian Liu, Xun Zhang, Song-Bo Univ Sci & Technol Liaoning Sch Elect & Informat Engn Anshan Liaoning Peoples R China

The objective of the Combined Economic Emissions Dispatch (CEED) problem is to reduce pollutant emissions by lowering the total cost of generating electricity while complying with all other constraints. The multiple objective functions of the CEED problem may be converted into a single objective by using a price penalty factor. Then it was solved with the arithmetic optimization algorithm (AOA) with three-dimensional chaotic mapping in spherical coordinate system. Firstly, five three-dimensional chaotic mappings in Cartesian coordinate system are embedded in the Mathematical optimization Accelerator (MOA) and the Mathematical optimization Probability (MOP) of the original algorithm. Secondly, 15 three-dimensional chaotic mappings in spherical coordinate system are constructed from the values of 5 three-dimensional chaotic mappings in Cartesian coordinate system through the mathematical expressions of mode length, polar angle and azimuth angle in spherical coordinate system. Then through a large number of simulation experiments, five best three-dimensional chaotic mappings in the spherical coordinate system are selected to be embedded into the two parameters (MOA and MOP) of the original algorithm to better balance the algorithm's global and local searching ability. The superiority of the improved algorithm is verified by employing 12 benchmark test functions in CEC2022. Eventually, the improved optimal algorithm (IAOA-r) to solve the power system CEED problem is tested on six generating units with four different loads (150 MW, 175 MW, 200 MW and 225 MW). The results of the improved algorithm are compared and analyzed with the results of the Reptile Search algorithm (RSA), Prairie Dog optimization (PDO), Bat algorithm (BAT), Whale optimization algorithm (WOA), Harris Hawk optimization (HHO), Rat Swarm optimization (RSO). The results demonstrate that the improved algorithm is capable of obtaining optimal fuel costs and smaller pollution emissions in every test case.

关键词： Combined economic emissions dispatch arithmetic optimization algorithm Three-dimensional chaotic mapping Spherical coordinate system

来源：评论

学校读者我要写书评

暂无评论

Image Registration Using the arithmetic optimization algorithm for Robotic Visual Servoing

引用

INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS 2025年第1期18卷 1-12页

作者： Kmich, Mohamed Harrade, Inssaf Karmouni, Hicham Sayyouri, Mhamed Askar, S. S. Abouhawwash, Mohamed Sidi Mohamed Ben Abdellah Univ Natl Sch Appl Sci Engn Syst & Applicat Lab Fes Morocco Cadi Ayyad Univ Natl Sch Appl Sci Marrakech Morocco King Saud Univ Coll Sci Dept Stat & Operat Res POB 2455 Riyadh 11451 Saudi Arabia Michigan State Univ Dept Computat Math Sci & Engn CMSE E Lansing MI 48824 USA Mansoura Univ Fac Sci Dept Math Mansoura 35516 Egypt

Visual servoing using image registration is a method employed in robotics to control the movement of a system using visual information. In this context, we propose a new intensity-based image registration algorithm (IBIR) that uses information derived from images acquired at different times or from different views to determine the parameters of the geometric transformations needed to align these images. The arithmetic optimization algorithm (AOA) is used to optimize these parameters, minimizing the difference between the images to be aligned. The proposed algorithm, Intensity-Based Image Registration via arithmetic Optimisation algorithm (IBIRAOA), is robust to image data fluctuations and perturbations and can avoid local optima. Simulation results prove the importance and efficiency of the proposed algorithm in terms of computation time and similarity of aligned images compared to other methods based on various metaheuristics. In addition, our results confirm a significant improvement in the trajectory of the wheeled mobile robot, thus reinforcing the overall effectiveness of our method in practical navigation and robotic control applications.

关键词： arithmetic optimization algorithm Image Registration Metaheuristic optimization algorithms Robotic Visual Servoing

来源：评论

学校读者我要写书评

暂无评论

A multi-threshold image segmentation method based on arithmetic optimization algorithm: A real case with skin cancer dermoscopic images

引用

JOURNAL OF COMPUTATIONAL DESIGN AND ENGINEERING 2025年第2期12卷 112-137页

作者： Hao, Shuhui Huang, Changcheng Chen, Yi Wang, Mingjing Liu, Lei Xu, Suling Chen, Huiling Wenzhou Univ Key Lab Intelligent Informat Safety & Emergency Zh Wenzhou 325035 Zhejiang Peoples R China Wenzhou Univ Technol Sch Data Sci & Artificial Intelligence Wenzhou 325000 Zhejiang Peoples R China Sichuan Univ Coll Comp Sci Chengdu 610065 Sichuan Peoples R China Ningbo Univ Affiliated Hosp Med Sch Dept Dermatol Ningbo 315020 Zhejiang Peoples R China

Multi-threshold image segmentation (MTIS) is a crucial technology in image processing, characterized by simplicity and efficiency, and the key lies in the selection of thresholds. However, the method's time complexity will grow exponentially with the number of thresholds. To solve this problem, an improved arithmetic optimization algorithm (ETAOA) is proposed in this paper, an optimizer for optimizing the process of merging appropriate thresholds. Specifically, two optimization strategies are introduced to optimize the optimal threshold process: elite evolutionary strategy (EES) and elite tracking strategy (ETS). First, to verify the optimization performance of ETAOA, mechanism comparison experiments, scalability tests, and comparison experiments with nine state-of-the-art peers are executed based on the benchmark functions of CEC2014 and CEC2022. After that, to demonstrate the feasibility of ETAOA in the segmentation domain, comparison experiments were performed using 10 advanced segmentation methods based on skin cancer dermatoscopy image datasets under low and high thresholds, respectively. The above experimental results show that the proposed ETAOA performs outstanding optimization compared with benchmark functions. Moreover, the experimental results in the segmentation domain show that ETAOA has superior segmentation performance under low and high threshold conditions.

关键词： meta-heuristic algorithms arithmetic optimization algorithm skin cancer multi-threshold image segmentation

来源：评论

学校读者我要写书评

暂无评论

Fuzzy Adaptive Sliding-Mode Control Optimized by an arithmetic optimization algorithm for a Quadrotor Drone With Chaotic Nonlinear Dynamics

引用

OPTIMAL CONTROL APPLICATIONS & METHODS 2025年第2期46卷 634-646页

作者： Mahmoodabadi, M. J. Ibrahim, M. Yousef Sirjan Univ Technol Dept Mech Engn Sirjan Iran Federat Univ Australia Sch Engn & Informat Technol Churchill Vic Australia

An optimal fuzzy adaptive sliding mode controller (OFASMC) is introduced in the present paper for stabilizing a quadrotor drone with chaotic and nonlinear dynamics. At first, control efforts related to the motor torques of the regarded quadrotor drone are determined by the sliding mode procedure as the main stabilizer. Next, using the gradient descent formulation as well as the chain derivative rule, the control gains are adapted through the system states. Then, human knowledge-based fuzzy systems are appropriately designed to set the control parameters for achieving more accurate results. The output errors and control efforts are minimized through the optimum values found for the effective coefficients of the controller by applying the arithmetic optimization algorithm (AOA). Simulation results clearly illustrate the effectiveness of the introduced strategy to stabilize the quadrotor drone system with and without external disturbances. Block diagram of theproposed optimal fuzzy adaptive sliding mode control for the quadrotor drone. image

关键词： adaptive control arithmetic optimization algorithm fuzzy system nonlinear quadrotor drone optimal control sliding mode control

来源：评论

学校读者我要写书评

暂无评论

Sparse compressed deep echo state network with improved arithmetic optimization algorithm for chaotic time series prediction

引用

EXPERT SYSTEMS WITH APPLICATIONS 2025年 259卷

作者： Wang, Hongbo Mo, Yuanbin Guangxi Minzu Univ Sch Artificial Intelligence Nanning 530006 Guangxi Peoples R China Guangxi Key Lab Hybrid Computat & IC Design Anal Nanning 530006 Guangxi Peoples R China

A sparse compressed deep echo state network (SCDESN) incorporating sparse input units, compressed sampling and principal component analysis (PCA) units is proposed in this paper, and theoretically proved the sufficient and necessary conditions to ensure the echo state characteristics of the proposed scheme. In addition, a hybrid arithmetic optimization algorithm based on matrix design strategy and boundary selection strategy (SVD-HAOA) was proposed to optimize the hyper-parameters of the SCDESN model, taking into account the characteristics of the SCDESN model. The steps and process for optimizing the hyper parameters of the SCDESN model using SVDHAOA were presented. Finally, the SCDESN model optimized by SVD-HAOA was experimentally and summarized on a classic benchmark dataset and two real-world chaotic time series. The outcomes of the simulation indicated that the suggested model surpassed alternative models in performance and enhanced computational efficiency while maintaining prediction accuracy. This model may serve as a viable alternative for real-world applications.

关键词： Echo state networks Hierarchical structure Deep learning arithmetic optimization algorithm Chaotic time series prediction

来源：评论

学校读者我要写书评

暂无评论

HSMAOA: An enhanced arithmetic optimization algorithm with an adaptive hierarchical structure for its solution analysis and application in optimization problems

引用

THIN-WALLED STRUCTURES 2025年 206卷

作者： Liu, Jingsen Zhao, Jianggui Li, Yu Zhou, Huan Henan Univ Henan Int Joint Lab Intelligent Network Theory & K Kaifeng 475004 Peoples R China Henan Univ Coll Software Kaifeng 475004 Peoples R China Henan Univ Inst Management Sci & Engn Kaifeng 475004 Peoples R China Henan Univ Business Sch Kaifeng 475004 Peoples R China

The arithmetic optimization algorithm (AOA) has recently gained significant attention as a novel meta-heuristic algorithm. However, it faces challenges such as premature convergence and entrapment in local optima when addressing complex optimization problems. To overcome these limitations, this paper proposes an enhanced AOA, termed the Self-Adaptive Hierarchical arithmetic optimization algorithm (HSMAOA). The proposed method integrates three key strategies: Firstly, a spiral-guided random walk mechanism is introduced to improve global search ability. Secondly, a novel adaptive hierarchy leader and follower mechanism is proposed, which establishes a complete multi-branch tree hierarchy with decreasing branching degrees within the population, thereby increasing information exchange among population individuals to escape local optima. Finally, a differential mutation strategy based on ranked selection is introduced to enhance candidate solution quality. HSMAOA's performance was evaluated on the CEC2022 test suite against some state-of-the-art algorithms. Results, including optimization accuracy analysis, convergence curves, and various statistical tests, demonstrate HSMAOA's superior optimization capability and robustness. In addition, tests on eight engineering structure optimization problems, including the pressure vessel design problem, the multiple disk clutch brake design problem, and the step-cone pulley problem, and so forth, further validate its effectiveness. Thus, HSMAOA shows strong competitiveness in complex optimization tasks and potential for a wide range of applications, and is an advantageous and promising alternative solution for optimization problems.

关键词： arithmetic optimization algorithm Random walk Adaptive hierarchical structure CEC2022 Engineering optimization problem

来源：评论

学校读者我要写书评

暂无评论

Performance analysis of multiple-input multiple-output orthogonal frequency division multiplexing system using arithmetic optimization algorithm

引用

COMPUTER STANDARDS & INTERFACES 2025年 92卷

作者： Deepa, R. Karthick, R. Velusamy, Jayaraj Senthilkumar, R. Nehru Inst Engn & Technol Dept Elect & Commun Engn Coimbatore Tamilnadu India KLN Coll Engn Dept Comp Sci & Engn Pottapalayam 630612 India Hindusthan Inst Technol Dept Comp Sci & Engn Coimbatore Tamil Nadu India

This research aims to optimize the interference mitigation and improve system performance metrics, such as bit error rates, inter-carrier interference (ICI), and inter-symbol interference (ISI), by integrating the Redundant Discrete Wavelet Transform (RDWT) with the arithmetic optimization algorithm (AOA). This will increase the spectral efficiency of MIMO-OFDM systems for ultra-high data rate (UHDR) transmission in 5 G networks. The most important contribution of this study is the innovative combination of RDWT and AOA, which effectively addresses the down sampling issues in DWT-OFDM systems and significantly improves both error rates and data rates in high-speed wireless communication. Fifth-generation wireless networks require transmission at ultrahigh data rates, which necessitates reducing ISI and ICI. Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) is employed to achieve the UHDR. The bandwidth and orthogonality of DWT-OFDM (discrete wavelet transform-based OFDM) are increased;however system performance is degraded due to down sampling. The redundant discrete wavelet transform (RDWT) is proposed for eliminating down sampling complexities. Simulation results demonstrate that RDWT effectively lowers bit error rates, ICI, and ISI by increasing the carrier-to-interference power ratio (CIR). The arithmetic optimization algorithm is used to optimize ICI cancellation weights, further enhancing spectrum efficiency. The proposed method is executed in MATLAB and achieves notable performance gains: up to 82.95% lower error rates and 39.88 % higher data rates compared to the existing methods. Conclusion: The integration of RDWT with AOA represents a significant advancement in enhancing the spectral efficiency of MIMO-OFDM systems for UHDR transmission in 5 G networks. The proposed method not only enhances system performance but also lays a foundation for future developments in high-speed wireless communication by addressing down sampl

关键词： Redundant discrete wavelet transform arithmetic optimization algorithm Enhanced spectral efficiency Discrete wavelet transform

来源：评论

学校读者我要写书评

暂无评论

Multi-strategy arithmetic optimization algorithm for global optimization and uncertain motion tracking

引用

CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS 2025年第1期28卷 1-28页

作者： Gao, Zeng Zhuang, Yi Gu, Jingjing Nanjing Univ Aeronaut & Astronaut Coll Comp Sci & Technol 29 Jiangjun Rd Nanjing 211106 Jiangsu Peoples R China

Previous trackers mostly assume that the target has a smooth motion and perform target matching within a local window. However, targets often exhibit uncertain movements in real-world scenarios. Once the tracked target undergoes abrupt motion and moves outside the predefined local window, these trackers often fail. To address this issue, this paper introduces a multi-strategy arithmetic optimization algorithm (MSAOA) for global optimization and uncertain motion tracking. MSAOA is a high-performance optimizer that effectively solves uncertain motion in visual tracking. For MSAOA, we first design a dynamic stratification strategy to divide the population into three subpopulations. Then the mathematical model of each subpopulation is modified to improve the exploration and exploitation performance. Finally, extensive experiments over 23 benchmark functions and CEC2020 benchmark problems show that MSAOA is better than other algorithms. For the MSAOA tracker (MSAOAT), we utilize the proposed MSAOA as a joint local sampling-global search to generate candidate targets and match the best targets by a fitness function. More importantly, we design a verifier to unite local sampling and global search to form a complete tracking framework, which can effectively address smooth and abrupt motion in visual tracking. The qualitative and quantitative analyses on the general motion group and the abrupt motion group demonstrate that the MSAOAT can outperform other trackers.

关键词： Uncertain motion tracking arithmetic optimization algorithm Dynamic stratification strategy Multi-strategy

来源：评论

学校读者我要写书评

暂无评论

Boosted arithmetic optimization algorithm with elite opposition-based pattern search mechanism and its promise to design microstrip patch antenna for WLAN and WiMAX

引用

INTERNATIONAL JOURNAL OF MODELLING AND SIMULATION 2025年第1期45卷 264-279页

作者： Ozmen, Hueseyin Ekinci, Serdar Izci, Davut Dicle Univ Dept Elect & Elect Engn Diyarbakir Turkiye Batman Univ Dept Comp Engn Batman Turkiye Middle East Univ MEU Res Unit Amman Jordan

This paper investigates the performance of a novel artificial intelligence optimization technique in terms of designing a small size antenna that can be used for WLAN and WiMAX applications. In this regard, a boosted version of the arithmetic optimization algorithm is constructed as a novel artificial intelligence optimization technique with the aid of pattern search and elite opposition-based learning mechanisms. The proposed boosted arithmetic optimization algorithm is demonstrated for its superior explorative and exploitative behavior using classical fixed-dimensional, multimodal, and unimodal benchmark functions. The performance of the boosted arithmetic optimization algorithm is then presented for a real-world engineering optimization problem. For the latter challenge, a small size antenna that can be used for WLAN and WiMAX applications is designed. The obtained simulation results show that a compact small-sized patch antenna operating at WLAN and WiMAX frequencies can successfully be designed with the proposed boosted arithmetic optimization algorithm. Comparative evaluation against the state-of-the-art shows that efficiency is increased significantly since a bandwidth increase of up to 21% is achieved even with a more than 39% reduction in size.

关键词： arithmetic optimization algorithm elite opposition-based learning pattern search microstrip patch antenna WLAN and WiMAX applications

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：