检索结果-内蒙古大学图书馆

A hybrid Ant Lion Optimization a*algorithm based lightweight deep learning framework for cyber attack detection in IoT environment

引用

COMPUTERS & ELECTRICAL ENGINEERING 2025年 122卷

作者： Gupta, Brij B. Gaurav, Akshat Attar, Razaz Waheeb Arya, Varsha Bansal, Shavi Alhomoud, Ahmed Chui, Kwok Tai Asia Univ Dept Comp Sci & Informat Engn Taichung Taiwan Kyung Hee Univ 26 Kyungheedae Ro Seoul 02447 South Korea Symbiosis Int Univ Symbiosis Ctr Informat Technol SCIT Pune India Univ Econ & Human Sci Warsaw Poland Ronin Inst Montclair NJ USA Asia Univ Int Ctr AI & Cyber Secur Res & Innovat CCRI Taichung 413 Taiwan Princess Nourah bint Abdulrahman Univ Management Dept Coll Business Adm POB 84428 Riyadh 11671 Saudi Arabia Lebanese Amer Univ Dept Elect & Comp Engn Beirut 1102 Lebanon Univ Petr & Energy Studies UPES Ctr Interdisciplinary Res Misraspatti 248007 Uttaranchal India Insights2Techinfo Chandigarh India Chandigarh Univ UCRD Chandigarh India Northern Border Univ Coll Sci Dept Comp Sci Ar Ar Saudi Arabia Hong Kong Metropolitan Univ HKMU Hong Kong Peoples R China

Internet of Things (IoTs) are integral part of Web3, in which they are used for information collecting and sharing. However, the limited storage capacity of IoT decides made them vulnerable to many types of cyber attacks. In this context, we proposed a hybrid deep learning model for the detection of cyber attacks in the IoT environment. The proposed approach used features selection technique for the selection of efficient features and Ant Lion Optimization a*algorithm for tuning the hyper-parameters. This hybrid approach model train for five epochs and detects the attack traffic with an accuracy of 97%, which makes it efficient and lightweight for IoT applications. The proposed model is also outperformed the standard machine learning and deep learning models.

关键词： IoT DoS attack Probe attack CNN Ant Lion Optimization a*algorithm

来源：评论

学校读者我要写书评

暂无评论

A non-iterative distributed approximate dynamic programming a*algorithm for frequency security-constrained stochastic economic dispatch

引用

INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2025年 166卷

作者： Feng, Xiangyong Lin, Shunjiang Liang, Yutao Liu, Yanghua Liu, Mingbo South China Univ Technol Sch Elect Power Engn Guangzhou 510640 Peoples R China China Southern Power Grid Co Ltd Elect Power Res Inst Guangzhou 510663 Peoples R China Guangdong Polytech Normal Univ Sch Electromech Engn Guangzhou 510665 Peoples R China

Due to uncertainties associated with the power output of offshore wind farms, the active power balance and frequency security control of power systems with lots of offshore wind farms are highly challenging. To address this problem, in this study, a new stochastic economic dispatch model of a power system with offshore wind farms considering the system frequency security constraints is established to obtain economic and secure dispatch decisions. Furthermore, the nonlinear convexity of frequency security constraints provides considerable theoretical support for the global optimality of decision-making, and a golden section search-based approximate linear constraint generation a*algorithm is designed to approximate nonlinear frequency security constraints for improving computational efficiency. Next, a non-iterative distributed approximate dynamic programming a*algorithm based on the equivalent projection method is designed for the distributed solution of the established model. In the a*algorithm, first, the model is decoupled from time periods. Next, the high-dimensional feasible region of the offshore wind farm optimization model is projected into a low-dimensional feasible region and substituted into the transmission grid optimization model, and solves the models of the transmission grid and the offshore wind farms sequentially to achieve the non-iterative distributed solution. Finally, case studies on a modified IEEE 39-bus system with two offshore wind farms and an actual provincial system with seven offshore wind farms demonstrate the effectiveness and superiority of the proposed model and a*algorithm, reducing solution time by over 86.4% compared to the alternating direction method of multipliers-based distributed approximate dynamic programming a*algorithm.

关键词： Offshore wind farm Frequency security constraint Stochastic economic dispatch Approximate dynamic programming a*algorithm Non-iterative distributed a*algorithm

来源：评论

学校读者我要写书评

暂无评论

Polynomial fuzzy information granule based α-triple I fuzzy reasoning a*algorithm and its short-term forecasting of time series

引用

INFORMATION SCIENCES 2025年 689卷

作者： Li, Fang Wang, Caifang Shanghai Maritime Univ Sch Sci Shanghai 201306 Peoples R China

Short-term forecasting of time series is an important research topic, which involves data characteristic capture and intelligent reasoning. For this topic, the Gaussian polynomial fuzzy information granule with interpretability is granulated on data, enabling the extraction of data trend characteristic, besides, the associate characteristic within the data is captured through building fuzzy association rule. Building upon the data characteristics captured in fuzzy information granule and fuzzy association rule, an intelligent reasoning a*algorithm called the fuzzy information granule based alpha-Triple I a*algorithm is proposed, where the membership degree of data to granule is considered in reasoning, and next the accurate level of deviation from data to granule can be inferenced. Based on the excavated data characteristics and a rational inference, a short-term forecasting model is established. Its superiority in terms of accuracy and reliability when compared to 7 other models in real time series has been tested. Notably, the prediction of the novel model is accurate because the function of FAR is identified from FAR's truth degree, which means the validity degree of prediction. The application of the proposed model for short-term forecasting holds a potential impact across various fields.

关键词： Polynomial fuzzy information granule alpha-Triple I a*algorithm Fuzzy association rule Fuzzy reasoning system Short-term forecasting

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 a*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 a*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 a*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 a*algorithm Enhanced spectral efficiency Discrete wavelet transform

来源：评论

学校读者我要写书评

暂无评论

Artificial satellite search: A new metaheuristic a*algorithm for optimizing truss structure design and project scheduling

引用

APPLIED MATHEMATICAL MODELLING 2025年 143卷

作者： Cheng, Min-Yuan Sholeh, Moh Nur Natl Taiwan Univ Sci & Technol Dept Civil & Construct Engn 43 Sec 4Keelung Rd Taipei 106 Taiwan

The Artificial Satellite Search a*algorithm (ASSA), a novel physics-based metaheuristic a*algorithm designed to emulate the dynamic motion of satellites within a search space, is introduced in this study. The ASSA uses satellites as candidate solutions, which dynamically update their positions to navigate toward the optimal solution. The a*algorithm simulates satellite behavior using medium Earth orbit and low Earth orbit trajectories, facilitating more effective exploration and exploitation of the search space by accounting for the diverse scenario's satellites encounter relative to the Earth over time. In addition, orbit control mechanism and quantum computing technique are incorporated into the ASSA to further enhance the computational efficiency. Two experiments were conducted to assess ASSA performance. First, the performances of ASSA and seven wellknown a*algorithms were benchmarked on thirty benchmark functions and the CEC-2020 test suite. ASSA outperformed all of the comparison a*algorithms on the Wilcoxon signed-rank test, earned the highest rank (scoring 2.21 and 3.27 on the thirty benchmark and CEC-2020 test suite functions, respectively) on the Friedman test, and solved 27 out of 30 functions with shorter computational times. Second, ASSA was applied to address three engineering problems, achieving the best weight for truss structure optimization and the highest success rates for project scheduling. In these practical engineering applications, ASSA not only exhibited superior performance compared to alternative methods but also required the fewest evaluations of objective functions. The robustness and ease of implementation of the ASSA makes this new a*algorithm a versatile solution for various numerical optimization challenges.

关键词： Artificial satellite search a*algorithm Metaheuristic optimization Orbit control mechanism Quantum computing Project scheduling Truss structure design

来源：评论

学校读者我要写书评

暂无评论

A Dynamic Nuclear Radiation Environment Path Planning Method Based on an Improved Ant Colony a*algorithm

引用

NUCLEAR TECHNOLOGY 2025年

作者： Xiang, Suo-Yi Zhou, Huai-Fang Huo, Jian-Wen Zhang, Hua Gu, Chao-Fan Southwest Univ Sci & Technol Sch Informat & Engn Mianyang 621010 Sichuan Peoples R China Southwest Univ Sci & Technol Sichuan Key Lab Special Environm Robot Mianyang 621010 Sichuan Peoples R China State Grid Guangyuan Power Supply Co Guangyuan 628000 Peoples R China

Minimum cumulative dose path planning is an important radiation protection measure to reduce the radiation exposure of robots in nuclear emergencies. However, when an emergency or accident occurs, the distribution of radiation doses in the environment changes dynamically, making the cumulative radiation dose of paths planned by traditional methods nonoptimal. This study proposes a Dijkstra-improved ant colony optimization a*algorithm (DIACO) to address this issue, combined with a segmented search method to achieve path planning in a dynamic radiation *** method transforms the minimal cumulative radiation dose path obtained by the Dijkstra a*algorithm into an increment of the initial pheromone distribution for the ant colony optimization (ACO) a*algorithm, improves the heuristic factor of the ACO a*algorithm, and incorporates the maximum-minimum ant system to enhance the a*algorithm's convergence *** results show that the proposed DIACO a*algorithm reduces the cumulative radiation dose of the obtained path by approximately 21.08%, the travel distance to the target by about 33.87%, and the number of turns by about 85.1% compared to the traditional ACO a*algorithm.

关键词： Minimum cumulative dose path planning radiation exposure radiation protection ant colony optimization a*algorithm dynamic radiation environment

来源：评论

学校读者我要写书评

暂无评论

Optimization of machining process route for internal joint parts using artificial fish swarm a*algorithm

引用

JOURNAL OF ADVANCED MECHANICAL DESIGN SYSTEMS AND MANUFACTURING 2025年第1期19卷

作者： Han, Jun Zhu, Junwei Zhang, Yang Zhao, Zhenyao An, Zexi Inner Mongolia Univ Sci Technol Coll Mech Engn 7 Alding Rd Baotou 014010 Inner Mongolia Peoples R China

This paper addresses the issue of low processing efficiency resulting from the intricate process of an internal joint component. To this end, it proposes an optimization of the processing route for the component through the implementation of an artificial fish swarm a*algorithm based on the existing process route. In accordance with the characteristics of the part, the processing element is meticulously delineated, a prudent processing element code is formulated, the adjacent processing elements of the same category are consolidated, and the process constraints of the part are scrutinized before and after the merger. A reasonable constraint matrix model is constructed. The objective function is to determine the minimum number of machine tool, cutting tool, and clamping type changes. The design of prey, swarm, and follow behavioral parameters is conducted in a reasonable manner, as is the optimization and adjustment of the a*algorithm. By comparing and verifying the pre-optimization and post-optimization process solutions, the study shows that the combined optimized solution reduces the total number of machine tool changes, tool changes, and clamping changes by 43.8% and reduces the total machining time by 7 minutes and 16 seconds, which is more efficient and reasonable.

关键词： Manufacturing feature Manufacturing step cell Constraint matrix Process optimization Artificial fish swarm a*algorithm

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 a*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 a*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 a*algorithms arithmetic optimization a*algorithm skin cancer multi-threshold image segmentation

来源：评论

学校读者我要写书评

暂无评论

Power system economic emission dispatch considering uncertainties of wind, solar, and small runoff hydropower via a hybrid multi-objective optimization a*algorithm

引用

EXPERT SYSTEMS WITH APPLICATIONS 2025年 278卷

作者： Xiong, Guojiang Liu, Qinghua Wang, Yang Fu, Xiaofan Guizhou Univ Coll Elect Engn Guiyang 550025 Peoples R China Minist Educ Key Lab Ind Internet Things & Networked Control Chongqing 400065 Peoples R China State Grid Chongqing Elect Power Co Wanzhou Power Supply Branch Chongqing 404100 Peoples R China

Economic emission dispatch (EED) plays a key role for the power system operation. With the integration of renewable energy sources (RESs), their uncertainties pose great challenges to the EED. This work establishes an EED model of thermal generators, wind, solar, and small runoff hydropower and considers varied practical factors and constraints. Overestimation and underestimation models are used to describe the uncertainties. Meanwhile, to solve this model effectively, a hybrid multi-objective method MOAGT by combining Archimedes optimization a*algorithm, artificial gorilla troops optimizer, and teaching-learning-based optimization is presented via both parallelization and serialization. Some techniques including chaotic opposition initialization, Morlet wavelet mutation, memory retention, and modified compromise solution selection are utilized to raise the performance. The validity of the proposed model with MOAGT is demonstrated on two systems. Results compared with peer a*algorithms and the CPLEX solver show that MOAGT achieves better solutions in less costs and lower emissions, which can make the systems run in a more economical and low-carbon state under the premise of meeting the system reliability. Besides, the established EED model has good portability that supports the transition to a cleaner energy system. Furthermore, MOAGT can be seen as an effective alternate to the EED problem with RESs.

关键词： Artificial gorilla troops optimizer Archimedes optimization a*algorithm Economic emission dispatch Renewable energy Teaching-learning-based optimization Uncertainty

来源：评论

学校读者我要写书评

暂无评论

Enhancing the analytical modeling of proton-exchange membrane fuel cells for optimal parameter extraction with the Ali Baba and the forty thieves a*algorithm

引用

JOURNAL OF THE TAIWAN INSTITUTE OF CHEMICAL ENGINEERS 2025年 172卷

作者： Linoubli, Lazhar Hajji, Salah Ben Messaoud, Ramzi Res & Technol Ctr Energy Lab Nanomat & Syst Renewable Energies BP 95Hammam Lif Ben Arous 2050 Tunisia Univ Tunis Higher Natl Engn Sch Tunis Tunis Tunisia

Background: This research presents an improvement in the analytical modeling of the equivalent electrical circuit of Proton-Exchange Membrane Fuel Cells (PEMFC). This enhancement is based on a more generalized theoretical framework than existing approaches, providing a more accurate representation of the fuel cell's electrical behavior. Methods: A new expression for the activation voltage has been developed from an improved solution to the Butler-Volmer equation, providing a more accurate representation of electrochemical kinetics without resorting to the Tafel approximation. Additionally, a generalized formulation of the reversible voltage, accounting for the presence of water vapor, along with adjustments to the concentration voltage, has been integrated to optimize the model's accuracy. The Ali Baba and The Forty Thieves (AFT) metaheuristic a*algorithm is employed for parameter extraction, ensuring efficient and robust model optimization. Significant Results: The proposed model demonstrates significantly higher accuracy, with Total Sum of Squares (SSE) values of 3.9083e(-08),5.9158e(-08), and 8.0147e(-10) for the commercial fuel cells NedStack, BCS 500, and Ballard, respectively. These values are considerably lower than the best results reported in the literature (2.2881x10(-2),1.1364e(-2),0.1486), demonstrating the enhanced reliability and precision of the proposed model.

关键词： Parameter estimation PEMFC modeling Butler-Volmer equation Ali baba and the forty thieves a*algorithm Activation voltage Concentration voltage And reversible voltage

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：