检索结果-内蒙古大学图书馆

3rd International Conference on Smart Computing and Informatics (SCI)

作者： Prathyusha, Damai Jessica Naseera, Shaik Anusha, D. J. Alisha, K. VIT Sch Comp Sci & Engn Vellore Tamil Nadu India Sri Padmavati Visvavidyalayam Tirupati Andhra Pradesh India Sree Vidhyanikethan Engn Coll Tirupati Andhra Pradesh India

ISBN: (纸本)9789813296909;9789813296893

Cloud computing offers internet-based services to access various on-demand resources by overcoming the necessity of centralized computing. There are plenty of challenges, like privacy, security, load balancing, resource provisioning, existing in this virtualized environment. Among them, security is one of the major complications. Concerning the security and privacy issues, distributed denial of service (DDoS) attacks can cause great damage to the availability of cloud services and resources. Till now, attack mitigation strategies residues is an on-going research challenge due to the attack tendency to advance in sophistication and ease of implementation. Moreover, cloud service customers, as well as providers, need to be observant in understanding the menaces of DDoS attacks. The crux of such attack mitigation mechanism is to assure early and fast detection of illegitimate entries into the network. To address such monitoring and detecting mechanism, this paper aims to address various nature-inspired algorithms which are having the propensity to resolve malware issues, such as DDoS attacks, naturally by offering an optimized solution.

关键词： biologically inspired algorithms Cloud security DDoS attacks Attack alleviation mechanisms Metaheuristic approach

来源：评论

学校读者我要写书评

暂无评论

Prediction of Electricity Consumption using biologically inspired algorithms 14

Prediction of Electricity Consumption using Biologically Ins...

引用

14th IEEE International Scientific Conference on Informatics

作者： Halas, Peter Loderer, Marek Rozinajova, Viera Slovak Univ Technol Bratislava Fac Informat & Informat Technol Bratislava Slovakia

ISBN: (纸本)9781538608890

Prediction of electricity consumption has become a very investigated field of research recently. By lowering prediction error, we can minimize costs of suppliers. The classical approach using one prediction model has been proved insufficient. The problem is that none of the currently existing prediction models is sufficiently robust to estimate the forecast of time series accurately. One of the solutions to this problem is Ensemble learning. This approach attempts to create the best possible prediction by employing several different forecasting methods. We focused particularly on the ways of combining these methods. We apply different swarm intelligence algorithms to find the optimal combinations. The aim of this study is to compare prediction accuracy of the ensemble learning model to base forecasting methods. We also examine the optimal size of forecasting methods in the ensemble.

关键词： time series prediction ensemble learning electricity consumption forecasting biologically inspired algorithms

来源：评论

学校读者我要写书评

暂无评论

Designing Effective Drug Therapies Using a Multiobjective Spider-Wasp Optimizer

引用

BIOMIMETICS 2025年第4期10卷 219-219页

作者： Nguyen, Trong-The Dao, Thi-Kien Nguyen, Van-Thien Pham, Duc-Tinh Fuzhou Inst Technol Sch Elect Engn Fuzhou 350506 Peoples R China Hanoi Univ Ind Sch Informat & Commun Technol Hanoi 10000 Vietnam

Designing effective drug therapies requires balancing competing objectives, such as therapeutic efficacy, safety, and cost efficiency-a task that poses significant challenges for conventional optimization methods. To address this, we propose the multi-objective spider-wasp optimizer (MOSWO), a novel approach uniquely emulating the cooperative predation dynamics between spiders and wasps observed in nature. MOSWO integrates adaptive mechanisms for exploration and exploitation to resolve complex trade-offs in multiobjective drug design. Unlike existing approaches, the algorithm employs a dynamic population-partitioning strategy inspired by predator-prey interactions, enabling efficient Pareto frontier discovery. We validate MOSWO's performance through extensive experiments on synthetic benchmarks and real-world case studies spanning antiviral and antibiotic therapies. Results demonstrate that MOSWO surpasses state-of-the-art methods (NSGA-II, MOEA/D, MOGWO, and MOPSO), achieving 11% higher hypervolume scores, 8% lower inverted generational distance scores, 9% higher spread scores, a 30% faster convergence, and superior robustness against noisy biological datasets. The framework's adaptability to diverse therapeutic scenarios underscores its potential as a transformative tool for computational pharmacology.

关键词： evolutionary algorithms multiobjective spider-wasp optimizer drug therapy design biologically inspired algorithms pareto optimization

来源：评论

学校读者我要写书评

暂无评论

A Survey on biologically inspired algorithms for Computer Networking

引用

IEEE COMMUNICATIONS SURVEYS AND TUTORIALS 2013年第3期15卷 1160-1191页

作者： Zheng, Chenyu Sicker, Douglas C. Univ Colorado Dept Comp Sci Boulder CO 80309 USA

biologically inspired algorithms (BIAs), processes that mimic how organisms solve problems, offer a number of attributes well suited to addressing challenges presented by future computer networking scenarios. Such future networks will require more scalable, adaptive and robust designs to address the dynamic changes and potential failures caused by high heterogeneity and large scale networks. A variety of biological algorithms demonstrate characteristics desirable to network design, and significant effort has been placed on analyzing and developing the corresponding BIAs and applying them to computer networking applications. This paper provides a comprehensive survey of BIAs for the computer networking field, in which different BIAs are organized and explored based on their: (1) biological source;(2) mathematical model;(3) major application;(4) advantages to corresponding "classic" approach;(5) limitations and border conditions;and (6) potential directions for future applications. The paper also compares performance amongst each type of BIA, and compares BIAs that are inspired by different biological sources but are applicable to similar networking applications. The paper concludes by offering a framework for understanding the application of BIAs to problems in the computer networking space.

关键词： self-organization biologically inspired algorithms computer networking artificial immune systems homeostasis cellular signaling networks chemotaxis and morphogenesis division of labor pattern formation corpse clustering and brood sorting foraging pulse-coupled oscillator information epidemics biological symbiosis predator-prey relationship

来源：评论

学校读者我要写书评

暂无评论

A Review of AI-based MANET Routing Protocols 19

A Review of AI-based MANET Routing Protocols

引用

19th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob)

作者： Safari, Fatemeh Savic, Izabela Kunze, Herb Ernst, Jason Gillis, Daniel Univ Guelph Sch Comp Sci Guelph ON Canada Univ Guelph Dept Math & Stat Guelph ON Canada

ISBN: (纸本)9798350336672

Developing scalable and robust routing protocols for Mobile ad hoc Networks (MANETs) can be challenging given issues related to limited energy, node mobility, and changing topology. While a variety of MANET routing protocols are available, they are often hindered by node mobility. Artificial Intelligence (AI) approaches (i.e. biologically inspired and machine learning algorithms) provide a novel approach to MANET routing problems that are better equipped to address these issues. These approaches can improve network performance by minimizing energy consumption, improving overhead, and more. This paper's main contribution is that it promotes the use of AI to provide high-performance routing protocols. Our work surveys both biologically inspired and machine learning approaches and discusses the contributions made to provide readers with a greater understanding of these approaches and methods that can be taken to improve routing and other performance metrics.

关键词： MANETs Routing biologically inspired algorithms Machine learning

来源：评论

学校读者我要写书评

暂无评论

A Visual Variability and Visuo-Tactile Coordination inspired Child Adaptation Mechanism for Wearable Age Group Recognition and Activity Recognition

ADVANCED INTELLIGENT SYSTEMS

引用

ADVANCED INTELLIGENT SYSTEMS 2023年第1期5卷

作者： Kang, Peiqi Li, Jinxuan Jiang, Shuo Shull, Peter B. Shanghai Jiao Tong Univ Sch Mech Engn State Key Lab Mech Syst & Vibrat Shanghai 200240 Peoples R China Tongji Univ Coll Elect & Informat Engn Shanghai 201804 Peoples R China Frontiers Sci Ctr Intelligent Autonomous Syst Shanghai 200120 Peoples R China

Not all wearable fitness devices are suitable for children. Due to the decay of activity recognition accuracy and exercise requirement variety caused by the physical differences between adults and children, devices developed for adults cannot provide appropriate exercise guidance to children. Considering the complexity and time-consuming nature of developing a new children-specific model, this article proposes a child adaptation mechanism that can be integrated into current adult wearable devices. Two algorithms using unlabeled children's data for age group recognition and activity recognition inspired by the visual variability in cognitive process and visuo-tactile coordination phenomenon in cortical plasticity are proposed. During an experiment on 30 adults and children, the age group recognition algorithm achieves 93.33% recognition accuracy, and the activity recognition algorithm achieves 88.57% recognition accuracy. This is an 11.16% improvement compared with the baseline and 2.87-4.1% improvement compared with the state-of-the-art transfer learning or self-adaptation algorithms. The proposed mechanism ameliorates current wearable devices with minimum cost to make them suitable for children and can serve as an alternative to help children learn healthy exercise habits. It is hoped that the work can draw the attention of academia to vulnerable groups, including children, to build a friendlier artificial intelligence network.

关键词： biologically inspired algorithms human activity recognition neural networks visuo-tactile coordination wearable sensor

来源：评论

学校读者我要写书评

暂无评论

Self-Stabilizing Task Allocation In Spite of Noise 20

Self-Stabilizing Task Allocation In Spite of Noise

引用

32nd ACM Symposium on Parallelism in algorithms and Architectures (SPAA)

作者： Dornhaus, Anna Lynch, Nancy Mallmann-Trenn, Frederik Pajak, Dominik Radeva, Tsvetomira Univ Arizona Dept Ecol & Evolutionary Biol Tucson AZ 85721 USA MIT CSAIL 77 Massachusetts Ave Cambridge MA 02139 USA Kings Coll London Dept Informat London England Wroclaw Univ Sci & Technol Wroclaw Poland

ISBN: (纸本)9781450369350

We study the problem of distributed task allocation by workers in an ant colony in a setting of limited capabilities and noisy environment feedback. We assume that each task has a demand that should be satisfied but not exceeded, i.e., there is an optimal number of ants that should be working on this task at a given time. The goal is to assign a near-optimal number of workers to each task in a distributed manner without explicit access to the value of the demand nor to the number of ants working on the task. We seek to answer the question of how the quality of task allocation depends on the accuracy of assessing by the ants whether too many (overload) or not enough (lack) ants are currently working on a given task. In our model, each ant receives a binary feedback that depends on the deficit, defined as the difference between the demand and the current number of workers in the task. The feedback is modeled as a random variable that takes values lack or overload with probability given by a sigmoid function of the deficit. The higher the overload or lack of workers for a task, the more likely it is that an ant receives the correct feedback from this task;the closer the deficit is to zero, the less reliable the feedback becomes. Each ant receives the feedback independently about one chosen task. We measure the performance of task allocation algorithms using the notion of inaccuracy, defined as the number of steps in which the deficit of some task is beyond certain threshold. We propose a simple, constant-memory, self-stabilizing, distributed algorithm that converges from any initial assignment to a near-optimal assignment under noisy feedback and keeps the deficit small for all tasks in almost every step. We also prove a lower bound for any constant-memory algorithm, which matches, up to a constant factor, the accuracy achieved by our algorithm.

关键词： ants biologically inspired algorithms noise task-allocation

来源：评论

学校读者我要写书评

暂无评论

A novel methodology for optimal single mobile robot scheduling using whale optimization algorithm

引用

APPLIED SOFT COMPUTING 2019年 81卷 105520-000页

作者： Petrovic, Milica Miljkovic, Zoran Jokic, Aleksandar Univ Belgrade Fac Mech Engn Dept Prod Engn Lab Ind Robot & Artificial Intelligence Kraljice Marije 16 Belgrade 11120 35 Serbia

One of the fundamental requirements for creating an intelligent manufacturing environment is to develop a reliable, efficient and optimally scheduled material transport system. Besides traditional material transport solutions based on conveyor belts, industrial trucks, or automated guided vehicles, nowadays intelligent mobile robots are becoming widely used to satisfy this requirement. In this paper, the authors analyze a single mobile robot scheduling problem in order to find an optimal way to transport raw materials, goods, and parts within an intelligent manufacturing system. The proposed methodology is based on biologically inspired Whale Optimization Algorithm (WOA) and is aimed to find the optimal solution of the nondeterministic polynomial-hard (NP-hard) scheduling problem. The authors propose a novel mathematical model for the problem and give a mathematical formulation for minimization of seven fitness functions (makespan, robot finishing time, transport time, balanced level of robot utilization, robot waiting time, job waiting time, as well as total robot and job waiting time). This newly developed methodology is extensively experimentally tested on 26 benchmark problems through three experimental studies and compared to five meta-heuristic algorithms including genetic algorithm (GA), simulated annealing (SA), generic and chaotic Particle Swarm Optimization algorithm (PSO and cPSO), and hybrid GA-SA algorithm. Furthermore, the data are analyzed by using the Friedman statistical test to prove that results are statistically significant. Finally, generated scheduling plans are tested by Khepera II mobile robot within a laboratory model of the manufacturing environment. The experimental results show that the proposed methodology provides very competitive results compared to the state-of-art optimization algorithms. (C) 2019 Elsevier B.V. All rights reserved.

关键词： Mobile robot Scheduling Whale optimization algorithm biologically inspired algorithms Intelligent manufacturing systems

来源：评论

学校读者我要写书评

暂无评论

Formal Analysis of HTM Spatial Pooler Performance Under Predefined Operation Conditions

Formal Analysis of HTM Spatial Pooler Performance Under Pred...

引用

International Joint Conference on Rough Sets (IJCRS)

作者： Pietron, Marcin Wielgosz, Maciej Wiatr, Kazimierz ACK Cyfronet AGH Ul Nawojki 11 PL-30950 Krakow Poland

ISBN: (纸本)9783319471600;9783319471594

This paper introduces mathematical formalism for Spatial Pooler (SP) of Hierarchical Temporal Memory (HTM) with a spacial consideration for its hardware implementation. Performance of HTM network and its ability to learn and adjust to a problem at hand is governed by a large set of parameters. Most of parameters are codependent which makes creating efficient HTM-based solutions challenging. It requires profound knowledge of the settings and their impact on the performance of system. Consequently, this paper introduced a set of formulas which are to facilitate the design process by enhancing tedious trial-and-error method with a tool for choosing initial parameters which enable quick learning convergence. This is especially important in hardware implementations which are constrained by the limited resources of a platform.

关键词： Hierarchical temporal memory Machine learning biologically inspired algorithms

来源：评论

学校读者我要写书评

暂无评论

Using biologically inspired computing to effectively improve prediction models

引用

International Journal of Hybrid Intelligent Systems 2016年第2期13卷 99-112页

作者： Ezzeddine, Anna Bou Lóderer, Marek Laurinec, Peter Vrablecová, Petra Rozinajová, Viera Lucká, Mária Lacko, Peter Grmanová, Gabriela Faculty of Informatics and Information Technology Slovak University of Technology in Bratislava Bratislava Slovak Republic

The complexity of certain problems causes that classicalmethods for finding exact solutions have some limitations. In this paper wepropose an incremental heterogeneous ensemble model for time seriesprediction where biologically inspired algorithms offer a suitablealternative. Ensemble learningtechniques are advantageously used forimproving performance of various prediction methods. The quality of thiskind of machine learning approaches depends on proper combination of usedmethods. The influence of each of the used method can change on the fly andis determined by proper choice of its weights. Finding optimal weights inprediction methods represents typical optimization problem with objectivefunction reflecting error minimization, where biologically inspiredalgorithms can be used. In the proposed paper, we study several biologicallyinspired algorithms in the process of weights optimization. We investigateand compare ensembles using base models and ensembles optimized bybiologically inspired algorithms. We demonstrate that the ensemble learningprediction models optimized by biologically inspired algorithms outperformedthe base prediction methods. We present performance and accuracy results ofproposed ensemble models that were evaluated on power load datasets withconcept drifts.

关键词： Ensemble learning time series prediction biologically inspired algorithms power load prediction

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：