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      Path planning of scenic spots based on improved A* algorithm

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          Abstract

          Traditional scenic route planning only considers the shortest path, which ignores the information of scenic road conditions. As the most effective direct search method to solve the shortest path in static road network, A* algorithm can plan the optimal scenic route by comprehensively evaluating the weights of each expanded node in the gridded scenic area. However, A* algorithm has the problem of traversing more nodes and ignoring the cost of road in the route planning. In order to bring better travel experience to the travelers, the above factors are taken into account. This paper presents a path planning method based on the improved A* algorithm. Firstly, the heuristic function of the A* algorithm is weighted by exponential decay to improve the calculation efficiency of the algorithm. Secondly, in order to increase the practicality of the A* algorithm, the impact factors that road conditions is introduced to the evaluation function. Finally, the feasibility of the improved A* algorithm is verified through simulation experiments. Experimental results show that the improved A* algorithm can effectively reduce the calculation time and road cost.

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          Ant system: optimization by a colony of cooperating agents.

          An analogy with the way ant colonies function has suggested the definition of a new computational paradigm, which we call ant system (AS). We propose it as a viable new approach to stochastic combinatorial optimization. The main characteristics of this model are positive feedback, distributed computation, and the use of a constructive greedy heuristic. Positive feedback accounts for rapid discovery of good solutions, distributed computation avoids premature convergence, and the greedy heuristic helps find acceptable solutions in the early stages of the search process. We apply the proposed methodology to the classical traveling salesman problem (TSP), and report simulation results. We also discuss parameter selection and the early setups of the model, and compare it with tabu search and simulated annealing using TSP. To demonstrate the robustness of the approach, we show how the ant system (AS) can be applied to other optimization problems like the asymmetric traveling salesman, the quadratic assignment and the job-shop scheduling. Finally we discuss the salient characteristics-global data structure revision, distributed communication and probabilistic transitions of the AS.
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            An Energy-Balanced Routing Method Based on Forward-Aware Factor for Wireless Sensor Networks

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                Author and article information

                Contributors
                463182358@qq.com
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                25 January 2022
                25 January 2022
                2022
                : 12
                : 1320
                Affiliations
                [1 ]GRID grid.412099.7, ISNI 0000 0001 0703 7066, College of Information Science and Engineering, , Henan University of Technology, ; Zhengzhou, 450001 China
                [2 ]GRID grid.488144.5, ISNI 0000 0004 7417 3852, School of Resources and Environmental Engineering, , Anshun University, ; Anshun, 561000 China
                [3 ]GRID grid.9227.e, ISNI 0000000119573309, State Key Laboratory of Cryospheric Science, Northwest Institute of Eco-Environment and Resources, , Chinese Academy Sciences, ; Lanzhou, 730000 China
                Article
                5386
                10.1038/s41598-022-05386-6
                8789847
                35079066
                b6b05c84-73c1-441c-bab3-1797b0413ef5
                © The Author(s) 2022

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 7 October 2021
                : 11 January 2022
                Funding
                Funded by: Key Laboratory of Grain Information Processing and Control (Henan University of Technology), Ministry of Education
                Award ID: KFJJ-2020-113
                Award ID: KFJJ-2020-113
                Award ID: KFJJ-2020-113
                Award ID: KFJJ-2020-113
                Award Recipient :
                Funded by: Science and Technology Cooperation Project of Anshun University
                Award ID: LH[2017]7059
                Award ID: LH[2017]7059
                Award ID: LH[2017]7059
                Award ID: LH[2017]7059
                Award Recipient :
                Funded by: Cultivation Programme for Young Backbone Teachers in Henan University of Technology
                Award ID: 21420070
                Award ID: 21420070
                Award ID: 21420070
                Award Recipient :
                Funded by: Key Projects of Science and Technology Research of Henan Province
                Award ID: 202102310334
                Award ID: 202102310334
                Award ID: 202102310334
                Award ID: 202102310334
                Award Recipient :
                Categories
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                Custom metadata
                © The Author(s) 2022

                Uncategorized
                computational science,computer science
                Uncategorized
                computational science, computer science

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