检索结果-内蒙古大学图书馆

Human-Computer Interaction, Optimization and Robotic Applications (HORA), International Congress on

作者： Ahmed A. Khalifa Shreyas J Gururaj H L Udayaprasad P K Srinidhi N N Department of Networking and Security College of Information Technology University of Fujairah Fujairah UAE Switching and Traffic Department National Telecommunication Institute Cairo Egypt Department of Information Technology Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal Karnataka India Department of Artificial Intelligence & Machine Learning Global Academy of Technology Bengaluru India Department of Computer Science & Engineering Manipal Institute of Technology Bengaluru Manipal Academy of Higher Education Manipal Karnataka India

ISBN: (数字)9798350394634

ISBN: (纸本)9798350394641

Futuristic demands of multimedia applications involve comprehensive sharing of dynamic data attributes within the Multimedia Items (IoMT) Internet sense. Exploring the existing research void in this area reveals need of building an integrated routing strategy for IoMT that can cope with multiple network characteristics, physical artifacts, and with cost-effective networks and distribution modules satisfy connectivity requirements. This paper suggest a layer cross architect-layerure optimization for IoMT applications with a emphasis on connectivity efficiency factors such as rising latency, energy limitations, and optimizing low-cost energy usage. The proposed work models and integrates a swarm intelligence paradigm which involve intelligent computing of artificial bee colony (ABC) maintaining effective link creation and selects the best path from source to target IoT nodes. The proposed research achieve the strongest routing usefulness for multimedia data exchange over IoT. To ensure this, the output of the proposed device is validated with an comprehensive simulation test. Results tested using MATLAB simulation method indicate an improvement of 8% in energy usage, 10% increase in throughput, 8% decrease in end to end delay and 10% increase in packet delivery ratio.

关键词： Cross layer design Energy consumption Routing Throughput artificial bee colony algorithm Delays Multimedia communication

来源：评论

学校读者我要写书评

暂无评论

Large-scale emergency medical services scheduling during the outbreak of epidemics

引用

ANNALS OF OPERATIONS RESEARCH 2025年第1期348卷 445-469页

作者： Wang, Lubing Zhao, Xufeng Wu, Peng Nanjing Univ Aeronaut & Astronaut Coll Econ & Management Nanjing 211106 Peoples R China Fuzhou Univ Sch Econ & Management Fuzhou 350108 Peoples R China

This paper studies a new large-scale emergency medical services scheduling (EMSS) problem during the outbreak of epidemics like COVID-19, which aims to determine an optimal scheduling scheme of emergency medical services to minimize the completion time of nucleic acid testing to achieve rapid epidemic interruption. We first analyze the impact of the epidemic spread and assign different priorities to different emergency medical services demand points according to the degree of urgency. Then, we formulate the EMSS as a mixed-integer linear program (MILP) model and analyze its complexity. Given the NP-hardness of the problem, we develop two fast and effective improved discrete artificial bee colony algorithms (IDABC) based on problem properties. Experimental results for a real case and practical-sized instances with up to 100 demand points demonstrate that the IDABC significantly outperforms MILP solver CPLEX and two state-of-the-art metaheuristic algorithms in both solution quality and computational efficiency. In addition, we also propose some managerial implications to support emergency management decision-making.

关键词： COVID-19 Nucleic acid testing Emergency management Medical service scheduling MILP artificial bee colony algorithm

来源：评论

学校读者我要写书评

暂无评论

Multi-objective multi-compartment vehicle routing problem of fresh products with the promised latest delivery time

引用

ANNALS OF OPERATIONS RESEARCH 2024年 1-33页

作者： Li, Xiufeng Tianjin Univ Coll Management & Econ Tianjin 300072 Peoples R China

In light of the growing consumer emphasis on delivery speed and corporate environmental responsibility, it becomes paramount to simultaneously address the alignment of customer expectations with corporate objectives. We undertake a comprehensive examination of delivery delays and carbon emissions stemming from e-commerce logistics, leading us to formulate a delivery delay penalty function informed by customer behavior traits such as loss aversion. Concurrently, we analyze various factors influencing customer satisfaction and integrate them into our model. Similarly, we incorporate multiple determinants impacting vehicle emissions, devising a logistics cost-minimization model encompassing carbon emissions and cooling expenses. By amalgamating considerations of customer satisfaction, logistics expenses, and environmental concerns, we devise a dual-objective optimization model. To tackle this complex challenge, we introduce a multi-objective artificial bee colony algorithm based on MOEA/D principles, substantiating its efficacy through extensive numerical experiments. Our findings demonstrate the algorithm's ability to intelligently optimize logistics routes, thus reducing vehicle utilization. Finally, we present a Pareto front, illustrating how mitigating customer satisfaction can alleviate logistics and carbon emission costs.

关键词： Fresh foods Time windows Low-carbon Multi-compartment Multi-objective artificial bee colony algorithm

来源：评论

学校读者我要写书评

暂无评论

Damage Identification algorithm of Hinged Joints for Simply Supported Slab Bridges Based on Modified Hinge Plate Method and artificial bee colony algorithms

引用

algorithmS 2018年第12期11卷 198-198页

作者： Liu, Hanbing He, Xin Jiao, Yubo Jilin Univ Coll Transportat Changchun 130025 Jilin Peoples R China Beijing Univ Technol Minist Educ Key Lab Urban Secur & Disaster Engn Beijing 100124 Peoples R China

Hinge joint damage is a typical form of damage occurring in simply supported slab bridges, which can present adverse effects on the overall force distribution of the structure. However, damage identification methods of hinge joint damage are still limited. In this study, a damage identification algorithm for simply supported hinged-slab bridges based on the modified hinge plate method (MHPM) and artificial bee colony (ABC) algorithms was proposed by considering the effect of hinge damage conditions on the lateral load distribution (LLD) of structures. Firstly, MHPM was proposed and demonstrated, which is based on a traditional hinge plate method by introducing relative displacement as a damage factor to simulate hinge joint damage. The effectiveness of MHPM was verified through comparison with the finite element method (FEM). Secondly, damage identification was treated as the inverse problem of calculating the LLD in damage conditions of simply supported slab bridges. Four ABC algorithms were chosen to solve the problem due to its simple structure, ease of implementation, and robustness. Comparisons of convergence speed and identification accuracy with genetic algorithm and particle swarm optimization were also conducted. Finally, hinged bridges composed of four and seven slabs were studied as numerical examples to account for the feasibility and correctness of the proposed method. The simulation results revealed that the proposed algorithm could identify the location and degree of damaged joints efficiently and precisely.

关键词： damage identification algorithm hinge joint damage modified hinge plate method artificial bee colony algorithm finite element analysis

来源：评论

学校读者我要写书评

暂无评论

Optimization of distribution paths in cold chain logistics management based on IFW-ABC algorithm

引用

INTELLIGENT DECISION TECHNOLOGIES-NETHERLANDS 2024年第3期18卷 1711-1726页

作者： Zhao, Mei Henan Coll Transportat Logist Sch Zhengzhou Peoples R China

The current cold chain logistics management and distribution routes generally face problems such as environmental pollution and high costs. Therefore, the study proposed an improved fireworks-artificial bee colony for optimizing delivery paths. Firstly, the artificial bee colony was improved by using neighborhood search. Secondly, for the optimal solution, the fireworks explosion operator was used for the final result search. The benchmark function validation showed that the proposed algorithm performed better than other algorithms in solving optimal value, average value, and standard deviation. In the simulation analysis of a fresh enterprise in China, the total delivery cost was reduced by an average of 3.30% and 4.93% compared to other algorithms, considering carbon emission and not considering it, respectively. This proposed algorithm had more advantages in reducing quality loss, pollutant emissions, and CE. Therefore, this improved fireworks-artificial bee colony can effectively reduce the economic costs and environmental pollution of cold chain logistics distribution routes. This ensures economic benefits while considering social benefits, achieving the optimal path planning for logistics distribution.

关键词： Logistics management artificial bee colony algorithm fireworks algorithm neighborhood search path optimization

来源：评论

学校读者我要写书评

暂无评论

A Solution to Improve the Detection of the Nominal Value of the Financial Market: A Case Study of the Alphabet Stocks

引用

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2024年第1期15卷 201-211页

作者： Li, Zhaohua Chang, Xinyue Henan Inst Technol Sch Management Xinxiang 453003 Henan Peoples R China Henan Inst Technol Sch Art & Design Xinxiang 453003 Henan Peoples R China

Given the regular occurrence of non-stationarity, non -linearity, and high levels of noise in time series data, predicting the value of stocks is a considerable difficulty. Traditional methods have the potential to enhance the precision of forecasting, although they concurrently introduce computational complexity, hence augmenting the probability of prediction inaccuracies. To effectively tackle a range of concerns, the existing body of research proposes a novel approach that combines a light gradient boosting machine, a machine learning methodology, with artificial bee colony optimization. In the context of the examined dynamic stock market, the proposed model demonstrated better efficiency and performance compared to alternative models. The recommended model exhibited optimal performance, characterized by a low error rate and high efficacy. The analysis utilized data about the stock of Alphabet over the period spanning from January 2, 2015, to June 29, 2023. The outcomes of the study provide evidence of the predictive accuracy of the proposed model in determining stock prices. The study's findings demonstrate how well the suggested model performs when it comes to correctly predicting stock prices. The proposed model presents a pragmatic methodology for evaluating and forecasting time series data about stock prices. The research's findings show that, in terms of forecast accuracy, the suggested model performs better than the methods currently in use.

关键词： Alphabet stock machine learning light gradient boosting machine optimization artificial bee colony algorithm

来源：评论

学校读者我要写书评

暂无评论

Optimizing Air Cargo Delivery Routes with a Modified artificial bee colony

Optimizing Air Cargo Delivery Routes with a Modified Artific...

引用

Science and Information Technology in Smart Administration (ICSINTESA), International Conference of

作者： Valeriana Lukitosari Sena Safarina Farhan Hafizh Sentot Didik Surjanto Laksmi Prita Wardhani Departement of Mathematics Sepuluh Nopember Institute of Technology Surabaya Indonesia

ISBN: (数字)9798350376111

ISBN: (纸本)9798350376128

Airplanes serve as the primary means of transporting valuable and urgent items. Minimizing the costs associated with shipping, transshipment, and airport operational expenses, network design and air cargo delivery routes should be planned. Determining the minimum-cost air cargo delivery scheme necessitates basing the delivery routes on airport network connections. A MATLAB-based mixed integer linear programming model for six Indonesian airports’ air cargo flight route selection was resolved using artificial bee colony (ABC), Modified ABC, and metaheuristic methods after implementation with the cplexmilp function. In numerical simulations, cplexmilp had the smallest objective value compared to ABC and Modified ABC, with decreases of 10.41% and 3.23%. 6.96% is the difference between the minimum objective values obtained using the Modified ABC and ABC algorithms. The Modified ABC algorithm outperforms the ABC algorithm in minimizing air cargo shipping costs.

关键词： Costs Sensitivity analysis Atmospheric modeling Computational modeling Heuristic algorithms artificial bee colony algorithm Approximation algorithms Airports Mathematical models Numerical models

来源：评论

学校读者我要写书评

暂无评论

Hybridizing bat algorithm with artificial bee colony for combined heat and power economic dispatch

引用

APPLIED SOFT COMPUTING 2018年 72卷 189-217页

作者： Murugan, R. Mohan, M. R. Rajan, C. Christober Asir Sundari, P. Deiva Arunachalam, S. KCG Coll Technol Dept EEE Madras 600097 Tamil Nadu India Anna Univ Dept EEE Madras 600025 Tamil Nadu India Pondicherry Engn Coll Dept EEE Pondicherry 605014 India Jubail Ind Coll Dept Elect & Elect Engn Technol Jubail Industrial City 31961 Saudi Arabia

This paper presents a new algorithm based on hybridizing Bat algorithm (BA) and artificial bee colony (ABC) with Chaotic based Self-Adaptive (CSA) search strategy (CSA-BA-ABC) to solve the large-scale, highly non-linear, non-convex, non-smooth, non-differential, non-continuous, multi-peak and complex Combined Heat and Power Economic Dispatch (CHPED) problems. The proposed hybrid algorithm has better capability to escape from local optima with faster convergence rate than the standard BA and ABC. The proposed algorithm works based on the three mechanisms. The first one is a novel adaptive search mechanism, in which one of the three search phases (BA phase, directed onlooker bee phase and modified scout bee phase) is selected based on the aging level of the individual's best solution (pbest). In this regard, ABC's phases can assist BA phase to search based on deeper exploration /exploitation pattern as an alternative. In periodic intervals, the second mechanism called as CSA updates algorithm control parameters using chaotic system based on prevailing search efficiency in the swarm. Lastly, the third mechanism is enhancing the algorithm performance by incorporating individual's directional information, habitat selection and self-adaptive compensation. The effectiveness and robustness of the proposed algorithm are tested on a set of 23 benchmark functions and three CHPED problems. The obtained results by the suggested algorithm in terms of quality solution, computational performance and convergence characteristic are compared with various algorithms to show the ability of the proposed approach and its robustness in finding a better cost- effective solution. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Combined heat and power economic dispatch artificial bee colony algorithm Bat algorithm Directional information Self-adaptive compensation Non-convex optimization

来源：评论

学校读者我要写书评

暂无评论

Residential Building Duration Prediction Based on Mean Clustering and Neural Network

引用

ADVANCES IN CIVIL ENGINEERING 2024年第1期2024卷

作者： Ji, Fanrong Nan, Yunquan Wei, Aifang Fan, Peiyan Luo, Zhaoyuan Song, Xiaoqing Shandong Jianzhu Univ Sch Management Engn Jinan 250101 Peoples R China Shandong Jianzhu Univ Coll Surveying & Geoinformat Jinan 250101 Peoples R China Univ Canberra Sch Design & Built Environm Canberra 2601 Australia

The duration of a residential building project will directly influence its successful implementation;hence, it is essential to estimate a reasonable timeframe. In this study, a genetic algorithm (GA) was employed to optimize and refine the weights and thresholds of a back propagation (BP) neural network, thereby creating a GA-BP neural network model. A dataset comprising 111 instances of residential building durations was gathered, segmented into 90 training sets and 21 test sets. The model was validated and assessed through root mean square error (RMSE), correlation coefficient (R), and average error rate, demonstrating that the GA-BP neural network model is effective in predicting the duration of residential buildings. To enhance the predictive accuracy of the GA-BP neural network model, this research utilized an artificial bee colony (ABC)-improved K-means clustering algorithm to categorize 111 experimental datasets and 33 new datasets. The results indicated that the ABC-K-means-GA-BP model exhibited robust generalization capabilities and high predictive accuracy, with the fitness function showing optimal performance after 10, 15, and 35 generations, and the best validation performances recorded as 0.0019156, 0.00035905, and 0.0036914. This validates that the proposed ABC-K-means-GA-BP neural network model significantly aids in forecasting the construction period of residential buildings, which holds substantial practical value for enhancing construction efficiency.

关键词： artificial bee colony algorithm BP neural network duration prediction genetic algorithm K-means clustering algorithm

来源：评论

学校读者我要写书评

暂无评论

A Real-Time Nature-Inspired Intrusion Detection in Virtual Environments: An artificial bees colony Approach Based on Cloud Model

引用

INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS 2024年第12期15卷 648-657页

作者： Ayanboye, Ayanseun S. Efiong, John E. Ajayi, Temitope O. Gbadebo, Rotimi A. Akinyemi, Bodunde O. Olajubu, Emmanuel A. Aderounmu, Ganiyu A. Obafemi Awolowo Univ Dept Comp Sci & Engn Ife Nigeria OBAFEMI AWOLOWO UNIV Dept Comp Sci & Engn CyberSCADA Res Lab Ife Nigeria Obafemi Awolowo Univ CyberSCADA Res Lab Africa Ctr Excellence OAU ICT Driven Knowledge OAK Pk Ife Nigeria

-Real-time intrusion detection in virtual environments is crucial for maintaining the security and integrity of modern computing infrastructures. This paper proposes a nature-inspired mathematical model designed to detect both known and unknown attacks on virtual machines, focusing on enhancing detection accuracy and minimizing false alarm rates. The proposed model, named Developed artificial bee colony Optimization Based on Cloud Model (DABCO_CM), is inspired by the foraging behavior of bee swarms and integrates principles from the artificial bee colony algorithm and the cloud model rooted in fuzzy logic theory. The model was simulated using the UNSW_NB15 datasets in Google Colab and benchmarked against an existing model. It achieved a detection accuracy of 97.98%, compared to the existing model's 95.35%. Sensitivity results showed 99.92% for the proposed model, compared to 96.90% for the existing model, while specificity increased to 93.86%, in contrast to the existing model's 90.71%. These findings demonstrate a 3.02% increase in sensitivity, a 2.63% increase in accuracy, and a 3.15% increase in specificity, highlighting the model's superior capability in detecting attacks and its potential to learn from unlabeled data, addressing key challenges in virtual machine security.

关键词： Real-time intrusion detection virtual environments artificial bee colony algorithm cloud model algorithms intrusion detection system feature selection classification swarm intelligence fuzzy logic DNN

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：