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11th International Conference on Wireless Communications, Networking and Mobile Computing (WiCOM 2015)

作者： Nuo Wei Ming Lei Shu Ming Yang Chang Fang Chen Shandong Provincial Key Laboratory of Computer Networks Jinan China

ISBN: (纸本)9781510821279

Time synchronization has received a great attention as its crucial parts in wireless sensor networks. To minimize the number of transmission packets and achieve energy efficiency, a time synchronization scheme based on ant colony algorithm (TSAC) is presented in this paper. By exploiting the principle of ant colony algorithm adjusting the pheromone dynamically and automatically, an optimum pair selection theme is designed to select the nodes synchronized by performing the pairwise synchronization, and all the other nodes could be synchronized by listening. The simulation results show that TSAC needs less message exchanges and provides more accuracy than other time synchronization algorithms.

关键词： ant Colony algorithm Time Synchronization Wireless Sensor Networks ant algorithm clock recovery Wireless sensor networks

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An integrity control model for mass data transmission under big data cloud storage

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INTERNATIONAL JOURNAL OF GRID AND UTILITY COMPUTING 2022年第4期13卷 387-393页

作者： Zhu, Zhengguo Anhui Vocat Coll City Management Hefei Anhui Peoples R China

In order to improve the control level of massive data transmission integrity, improve the space utilisation efficiency and data transmission integrity under cloud storage, an integrity control model of mass data transmission under big data cloud storage is constructed. Firstly, the basic principle of big data cloud storage is studied. The developing process of big data, data storage technology, and data retrieval technology is studied. Secondly, the mass data feature extraction model is established. The theory model and framework of feature extraction model for mass data are analysed. Thirdly, the massive data integrity control algorithm is designed based on an ant algorithm. The prior control models of single node rate are studied and system level parallel data transmission rate are analysed. Finally, simulation analysis is carried out, and the effectiveness of the proposed method is verified.

关键词： integrity control mass data transmission big data cloud storage extraction model ant algorithm

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Simultaneous management of water and wastewater using ant and artificial neural network (ANN) algorithms

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INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY 2019年第10期16卷 5835-5856页

作者： Rastegaripour, F. Saboni, M. S. Shojaei, S. Tavassoli, A. Univ Torbat Heidarieh Dept Agr Econ Torbat Heidarieh Iran Univ Mashhad Dept Agr Econ Mashhad Razavi Khorasan Iran Islamic Azad Univ Zahedan Branch Young Researchers & Elite Club Zahedan Iran Payame Noor Univ Dept Agr Zahedan Iran

In the present study, simultaneous management of water and wastewater was examined using ant and artificial neural network algorithms. ant algorithm is one of the most meta-heuristic algorithms to solve optimization problems. The data were collected in a monthly time series from the Regional Water Organization of Khorasan Razavi during 1998-2016. Water flow data were initially estimated in the study. In this regard, different structures of the back propagation network (1, 2, 3, 4 and 5 nodes in the hidden layer) were designed by using logistic activation function in order to evaluate the efficiency of ANN model and its comparison with the ARIMA method in predicting the time series of the flows for the time horizons of next 3, 6, 9 and 12 month. The output data of each network were finally compared with actual data to evaluate the efficiency of the model and its comparison with ARIMA model using the evaluation criteria of models. Water resources were, then, allocated to drinking, agricultural and industrial sectors using the ant algorithm. According to the results of the total consumption of drinking water for the industrial sector, the southeast and northwest of Mashhad have the greatest amount of water. In other words, the northeastern and southwestern parts of Mashhad have the least amount of water for the industrial sector. And so, there must be a higher priority to water scarcity in these two regions than the other areas.

关键词： ant algorithm Artificial neural network Water Wastewater Mashhad plain

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Development Of Road Anomaly Data Transmission Using ant Colony Optimization algorithm in a Vehicle-To-Vehicle Communication

Development Of Road Anomaly Data Transmission Using Ant Colo...

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International Conference on Electronics, Computer and Computation (ICECCO)

作者： Muktar MT. Othman Steve A. Adeshina Moussa M. Boukar Department of Electrical and Electronics Engineering Nile University of Nigeria Abuja Nigeria Department of Computer Engineering Nile University of Nigeria Abuja Nigeria

ISBN: (数字)9781728151601

ISBN: (纸本)9781728151618

This study aim is to design a road anomaly transmission algorithms using ant Colony optimization (ACO) based Technique in a Vehicle-to-Vehicle (V2V) and Vehicle to Infrastructure (V2I) Communication. The developed VACO also uses the features of VANET to find out the optimal path by considering a minimum number of nodes and cost parameters, which provides information related to accidents, speed of neighbouring vehicle and weather to help users in making informed decisions. Vehicle routing protocol based on ACO (VACO) also ensures to mitigate issues by combining the reactive and proactive approach and considers the parameters affecting the Quality of Service (QoS) such as latency, bandwidth, and delivery ratio in evaluating the algorithms.

关键词： ant colony optimisation quality of service routing protocols vehicular ad hoc networks Quality of service V2V ant colony optimization Routing protocols Vehicle to vehicle communications VEHICULAR COMMUNICATIONS ant algorithm vehicle anomaly Road ADMINISTRATIVE CONSENT ORDER data transmission algorithms

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A new moving target interception algorithm for mobile robots based on sub-goal forecasting and an improved scout ant algorithm

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APPLIED SOFT COMPUTING 2013年第1期13卷 539-549页

作者： Zhu, Qingbao Hu, Jun Henschen, Larry Nanjing Normal Univ Sch Comp Sci Nanjing 210097 Jiangsu Peoples R China Northwestern Univ Evanston IL 60208 USA

It is difficult to make a robot intercept a moving target, whose trajectory and speed are unknown and dynamically changing, in a comparatively short distance when the environment contains complex objects. This paper presents a new moving target interception algorithm in which the robot can intercept such a target by following many short straight line trajectories. In the algorithm, an intercept point is first forecasted assuming that the robot and the target both move along straight line trajectories. The robot rapidly plans a navigation path to this projected intercept point by using the new ant algorithm. The robot walks along the planned path while continuously monitoring the target. When the robot detects that the target has moved to a new grid it will re-forecast the intercept point and re-plan the navigation path. This process will be repeated until the robot has intercepted the moving target. The simulation results have shown that the algorithm is very effective and can successfully intercept a moving target while moving along a relatively short path no matter whether the environment has complex obstacles or not and the actual trajectory of the moving target is a straight line or a complex curve. (C) 2012 Elsevier B. V. All rights reserved.

关键词： Mobile robot Moving target Interception Robot path planning ant algorithm

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Improving the Efficiency of Information Flow Routing in Wireless Self-Organizing Networks Based on Natural Computing

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ENERGIES 2021年第8期14卷 2255-2255页

作者： Przystupa, Krzysztof Pyrih, Julia Beshley, Mykola Klymash, Mykhailo Branytskyy, Andriy Beshley, Halyna Pieniak, Daniel Gauda, Konrad Lublin Univ Technol Dept Automat PL-20618 Lublin Poland Lviv Polytech Natl Univ Dept Telecommun UA-79013 Lvov Ukraine Univ Econ & Innovat Lublin Dept Mech & Machine Bldg PL-20209 Lublin Poland

With the constant growth of requirements to the quality of infocommunication services, special attention is paid to the management of information transfer in wireless self-organizing networks. The clustering algorithm based on the Motley signal propagation model has been improved, resulting in cluster formation based on the criterion of shortest distance and maximum signal power value. It is shown that the use of the improved clustering algorithm compared to its classical version is more efficient for the route search process. ant and simulated annealing algorithms are presented to perform route search in a wireless sensor network based on the value of the quality of service parameter. A comprehensive routing method based on finding the global extremum of an ordered random search with node addition/removal is proposed by using the presented ant and simulated annealing algorithms. It is shown that the integration of the proposed clustering and routing solutions can reduce the route search duration up to two times.

关键词： ant algorithm simulated annealing k-means signal-to-noise ratio (SNR)

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Research on Tourist Route based on a Novel ant Colony Optimization algorithm

Research on Tourist Route based on a Novel Ant Colony Optimi...

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IEEE International Conference on Power, Intelligent Computing and Systems

作者： Naixin Yang Yuliang Shi School of Beijing University of Technology

ISBN: (纸本)9781728137216

ant Colony Optimization (ACO) algorithm is a kind of subject-based intelligent algorithm with positive feedback mechanism and strong ability to find and optimize. The travel recommendation system is recognized as one of the technologies that can effectively solve the problem of information overload. This paper introduces an improved ant colony algorithm based on multi-objective decision-making to recommend the travel route to meet the needs of users. In this algorithm, the ant uses the attraction rating information that meets the user's needs and the actual distance of the attraction to find the shortest path. In order to prove the accuracy of the algorithm recommendation, an experiment is conducted on a network of attractions. The experimental results show that the algorithm can provide high quality solutions and can be effectively applied in the travel recommendation system.

关键词： Travel recommendation Multi-objective decision ACO algorithm Attraction rating ant algorithm algorithms ant colony optimization Recommender systems actual distance travel Attraction shortest path Consumers multi-objective control Pareto optimisation feedback mechanism

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Megapolis as a Symbiosis of Socio-Economic Ecosystems: The Role of Collaboration

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Journal of Open Innovation: Technology, Market, and Complexity 2022年第3期8卷

作者： Tolstykh, Tatyana Gamidullaeva, Leyla Shmeleva, Nadezhda Gromov, Sergey Ermolenko, Alexander Department of Industrial Strategy National University of Science & Technology (MISIS) Moscow 119049 Russian Federation Department of the Industrial Economics Plekhanov Russian University of Economics Moscow 119049 Russian Federation Department of Marketing Commerce and Services Penza State University Penza 440026 Russian Federation Department of Economics National University of Science & Technology (MISIS) Moscow 119049 Russian Federation Department of Automated Control Systems National University of Science & Technology (MISIS) Moscow 119049 Russian Federation Independent Researcher Krasnodar 350001 Russian Federation

In recent years, smart and ecological urbanism and transformations into the new models of city making have become a global mainstream. These are models of the smart city, the eco-city, and the eco-megacity. The article proposes a conceptual approach to the formation of the eco-megacity as a qualitatively new phenomenon in the post-industrial economy. The prerequisites for the transformation of a megapolis into an eco-megacity have been analyzed. The key characteristics of the new phenomenon have been revealed. The role of collaboration as the main factor in increasing the efficiency of interaction processes between ecosystem actors and between ecosystems themselves has been presented. The relationship of the formed ecosystem approaches and the groups of actors during implementation of an institutional project in the megapolis have been determined. It allows for the transformation of a megapolis into an eco-megacity. The ant colony optimization algorithm for studying the symbiosis of socio-economic ecosystems in the megapolis has been proposed. The authors have attempted to contribute to the development of theoretical and methodological aspects of the emerging eco-megacity concept as a new phenomenon of the modern economy. © 2022 by the authors.

关键词： ant algorithm collaboration process eco-megacity ecosystem approach institutional approach megapolis transformation symbiosis

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An ant algorithm for Solving the Four-coloring Map Problem

An Ant Algorithm for Solving the Four-coloring Map Problem

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9th International Conference on Natural Computation (ICNC)

作者： Chen, Hongshun Zhou, Peng Beijing Normal Univ Sch Informat Technol Zhuhai 519087 Peoples R China

ISBN: (纸本)9781467347143

An undirected graph can demonstrate adjacency relationships among regions in a planar map, and the four-coloring map problem is then converted into a graph vertex coloring problem with constraints. In order to solve the graph vertex coloring problem, an ant algorithm hybridized with a greedy algorithm was proposed. In this algorithm, ants in an ant colony with a given size separately move from one vertex to another according to their transition probability, and a greedy algorithm is used to initialize the proposed algorithm for improving its efficiency. Finally, the improved algorithm was tested by coloring the administrative map of Hunan Province, China, and results show that it is good at finding the optimal value, speed and stability.

关键词： four-coloring problem graph coloring problem ant algorithm combinatorial optimization

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SIMiner: A Stigmergy-Based Model for Mining Influential Nodes in Dynamic Social Networks

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IEEE TRANSACTIONS ON BIG DATA 2019年第2期5卷 223-237页

作者： Li, Weihua Bai, Quan Zhang, Minjie Auckland Univ Technol Sch Engn Comp & Math Sci Auckland New Zealand Univ Wollongong Sch Comp & Informat Technol Wollongong NSW 2522 Australia

With the widespread of the Internet, the on-line social network with big data is rapidly developing over time. Many enterprises attempt to develop their business by utilizing the power of on-line social networking platforms. A considerable amount of work has focused on how to select a set of influential users to maximize a kind of positive influence in static social networks. However, networks evolve, and the topological structure changes over time. How to mine and adapt the influencers in a dynamic and large-scale environment becomes a challenging issue. In this paper, a collective intelligence model, i.e., stigmergy-based influencers miner, is proposed to investigate influential nodes in a fully dynamic environment. The proposed model is capable of analysing influential relationships in a social network in decentralized manners and identifying the influencers more efficiently than traditional seed selection algorithms. Moreover, it is capable of adapting the solutions in complex dynamic environments without any interruptions or recalculations. Experimental results show that the proposed model achieves better performance than other traditional models in both static and dynamic social networks by considering both efficiency and effectiveness.

关键词： ant algorithm stigmergy multi-agent system influence maximization

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