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Intelligent planning of ship route in complex waters based on chaos genetic algorithm

INTERNET TECHNOLOGY LETTERS 2024年第1期7卷

作者： Jia, Lixiao Wang, Jiantao Guo, Yunlong Jiangsu Shipping Coll Sch Naut Technol Nantong 226010 Peoples R China

Pathway production of products has more splendid trail and route optimization specifications and the desire to prevent barriers in near real-time. This document presents a hybrid route planning approach for solving function optimization in cruise liners without a man. This research considers the problem of shipway making plans in depth and experiments it. Mathematical concepts for optimization algorithm decided to Complex Waters Based on chaos Genetic algorithm (CWCGA) is designed for ship trajectory tracking. Firstly, an enhanced particulate swarm algorithm is being used to design the pathways;an inter-process is founded on balancing the inhabitants' significant search capability and the query capacity at a local level. Last, the original paddle plan and global status are simulated. The Optimization problem is utilized for the very next part to plan this same path of the marine ecosystem. The results reveal that the improved algorithm performs better than the route plan method based on the linear enhancement of the particular search space's body mass.

关键词： chaos algorithm complex waters elaborate water marine ecosystem optimization path planning ship route unmanned aerial vehicle

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The Application of the Improved chaos algorithm in the Sports Performance Prediction

The Application of the Improved Chaos Algorithm in the Sport...

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2017 International Conference on Sports,Arts,Education and Management Engineering(SAEME 2017)

作者： Suqiong Feng Sichuan Agricultural University

ISBN: (纸本)9781510845831

With the continuous progress of the science, the physical training is also gradually scientific. As a kind of important sports phenomenon and rule, the statistics and the quantitative analysis method in the sports fieldwill be paid more and more attention by people. During the training process, using the scientific methods to predict the sports performance can find out the game rules of the players and make the training plans. In this paper, we use the chaos prediction method to predict the sports performance. In order to improve the performance of the algorithm, we improve the traditional chaos prediction algorithm and propose the improved chaos algorithm. According to the examples, we analyse the accuracy of the prediction.

关键词： Physical Training Training plan chaos algorithm

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Robot trajectory planning method based on genetic chaos optimization algorithm 18

Robot trajectory planning method based on genetic chaos opti...

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18th International Conference on Advanced Robotics (ICAR)

作者： Zhang, Qiwan Yuan, Mingting Song, Rui Qingdao Univ Dept Control Engn Qingdao Shandong Peoples R China Shandong Univ Robot Res Ctr Jinan Shandong Peoples R China

ISBN: (纸本)9781538631577

In order to smooth the trajectory of the robot end effector and optimize the running time of the robot, the paper presents a new robot trajectory planning method based on genetic chaos optimization algorithm. Firstly, the planned quintic polynomial is used to interpolate the position nodes in joint space to model the running trajectory of the robot. Subsequently, genetic chaos optimization algorithm based on genetic algorithm and chaos algorithm is introduced. Finally, it is proved that the novel method can make the running trajectory of the robot end effector smooth and time optimal under the constraints of velocity, acceleration and jerk through simulation and analysis.

关键词： Terms Robot Trajectory planning Genetic algorithm chaos algorithm Optimal time

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A binary dandelion algorithm using seeding and chaos population strategies for feature selection

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APPLIED SOFT COMPUTING 2022年第0期125卷

作者： Zhao, Yuxin Dong, Junwei Li, Xiaobo Chen, Hui Li, Shaolang Zhejiang Normal Univ Coll Math & Comp Sci Jinhua 321004 Peoples R China

Feature selection (FS) is an important pre-processing step in data mining and pattern recognition. It can effectively compress the dimensionality of the feature space to reduce computation time and improve classification performance. The meta-heuristic algorithm-based feature selection method by finding the optimal set of features in the solution space has been widely used. However, this method is prone to trap into local optimality in a sufficiently large solution space. In this paper, we first propose a binary dandelion algorithm (BDA) to improve classification accuracy. In addition, to improve the performance of the algorithm, a binary dandelion algorithm using an improved seeding strategy and chaotic populations (SBDA) is proposed in this paper. Firstly, the strategy of optimizing the seeding radius by using the vibrational function and the historical optimal population increases the complexity of the search process and improves the search performance of the algorithm in the solution space. Secondly, when generating seeds, chaotic populations are generated using chaotic operators, which improves the ability of the algorithm to jump out of the local optimum and improves the stability of the algorithm. In this paper, 15 well-established datasets collected from the UCI machine learning database were adopted to compare four variants of BDA using only chaotic population improvement and in the next experiments, both mechanisms are verified to be effective in improving the performance of the algorithm. In addition, this paper compares the proposed BDA algorithm and SBDA algorithm with eight other classical algorithms. The experimental results show that SBDA can obtain fewer features with higher classification accuracy in most cases. (C) 2022 Elsevier B.V. All rights reserved.

关键词： Metaheuristic algorithm Dandelion algorithm Feature selection Seeding strategy chaos algorithm

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A chaos-coupled multi-objective scheduling decision method for liner shipping based on the NSGA-III algorithm

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COMPUTERS & INDUSTRIAL ENGINEERING 2022年 174卷

作者： Ma, Weihao Zhang, Jinfeng Han, Yueyi Zheng, Huarong Ma, Dongfang Chen, Mingzhang Zhejiang Univ Ocean Coll Zhoushan Peoples R China Hainan Inst Zhejiang Univ Sanya Peoples R China Key Lab Ocean Observat Imaging Testbed Zhejiang Pr Zhoushan Peoples R China Minist Educ Engn Res Ctr Ocean Sensing Technol & Equipment Zhoushan Peoples R China Wuhan Univ Technol Sch Nav Wuhan Peoples R China Natl Univ Singapore Dept Mech Engn 9 Engn Dr 1 Singapore 117575 Singapore Zhejiang Univ Ocean Coll Zhoushan CampusZhihai Bldg 2121 Zheda Rd Zhoushan 316021 Peoples R China

Reducing sailing costs, time and emissions are three important decision-making objectives for ship operators. In this paper, a multi-objective decision model for liner shipping is established to optimize ship route, speed and number of ships deployed based on the three objectives. Moreover, the above model also takes into consideration the three latest ship emission reduction policies, including Emission Control Area, the 2020 Sulfur Limit Order and maritime Carbon Emission Taxation regulations. To solve the multi-objective scheduling problem, an improved non-dominated sorting genetic algorithm-III (NSGA-III) algorithm based on a chaos mechanism is proposed to find the Pareto solutions. And then a Multi-Criteria Decision Making (MCDM) method, the Hyperplane-based ranking method (HYRM) is developed to find the trade-off solution from the Pareto solutions. The proposed method was applied to two liner shipping service routes around southeast Asia and eastern United States, the results show that the proposed method can simultaneously reduce sailing costs, time and ship emission according to the users' preferences, and it can help shipping companies cope with fuel price fluctuations effectively.

关键词： Multi-objective optimization chaos algorithm NSGA-III Sailing cost time and emissions Hyperplane-based ranking method

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chaos Glowworm Swarm Optimization algorithm Based on Cloud Model for Face Recognition

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INTERNATIONAL JOURNAL OF PATTERN RECOGNITION AND ARTIFICIAL INTELLIGENCE 2020年第12期34卷

作者： Zhou, Guangyu Ouyang, Aijia Xu, Yuming Ningbo Univ Finance & Econ Coll Digital Technol & Engn Ningbo 315175 Zhejiang Peoples R China Zunyi Normal Univ Sch Informat Engn Zunyi 563006 Guizhou Peoples R China Changsha Normal Univ Coll Informat Sci & Engn Changsha 410082 Hunan Peoples R China

To overcome the shortcomings of the basic glowworm swarm optimization (GSO) algorithm, such as low accuracy, slow convergence speed and easy to fall into local minima, chaos algorithm and cloud model algorithm are introduced to optimize the evolution mechanism of GSO, and a chaos GSO algorithm based on cloud model (CMCGSO) is proposed in the paper. The simulation results of benchmark function of global optimization show that the CMCGSO algorithm performs better than the cuckoo search (CS), invasive weed optimization (IWO), hybrid particle swarm optimization (HPSO), and chaos glowworm swarm optimization (CGSO) algorithm, and CMCGSO has the advantages of high accuracy, fast convergence speed and strong robustness to find the global optimum. Finally, the CMCGSO algorithm is used to solve the problem of face recognition, and the results are better than the methods from literatures.

关键词： chaos algorithm cloud model face recognition function optimization global optimization glowworm swarm optimization

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Research on the Application of Improved Genetic algorithm Based on Physical Education Teaching 24

Research on the Application of Improved Genetic Algorithm Ba...

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International Conference on Computer and Multimedia Technology (ICCMT)

作者： Liu, Chen Yang, Ning Shan Dong Youth Univ Polit Sci Jinan Shandong Peoples R China

ISBN: (纸本)9798400718267

In the domain of physical education pedagogy, the orchestration of curricula commonly presents intricate optimization conundrums, the crux of which lies in the efficacious and rational employment of limited resources and temporal allotments. The utilisation of genetic algorithms has shown promise in addressing such challenges;however, to further enhance the performance of these algorithms and the practical efficacy of their applications, refinements have been made to the genetic algorithm itself. This treatise delves into an augmented genetic algorithm infused with the principles of chaos theory and provides a comprehensive exposition of its deployment in the scheduling of physical education classes. Within this enhanced algorithmic framework, chaotic mapping is employed to optimize the generation of the initial population, thereby bolstering its diversity. Chaotic crossover and mutation strategies have been devised with the aim of circumventing premature convergence and maintaining the effective exploration during the search process. The experimental segment collated multiple sets of physical education curriculum data, facilitating a comparative analysis of the performances between the conventional genetic algorithm and the revised variant. Subsequent to meticulous parameter optimization and multiple iterative cycles, the results have indicated that the refined algorithm furnishes a superior resolution to curriculum scheduling quandaries-not only ameliorating the quality of the optimization but also accelerating convergence. This scholarly work not only provides a viable solution to real-world problems within the sphere of physical education teaching but also extends new horizons for the application of genetic algorithms.

关键词： Genetic algorithm chaos algorithm Physical education Application research

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Security System for Surveillance Radar Network Communication Using chaos algorithm 8

Security System for Surveillance Radar Network Communication...

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8th International Conference on Telecommunication Systems Services and Applications (TSSA)

作者： Lestriandoko, Nova Hadi Juhana, Tutun Munir, Rinaldi Indonesian Inst Sci LIPI Res Ctr Informat Jakarta Indonesia ITB Sch Elect Engn & Informat Jawa Barat Indonesia

ISBN: (纸本)9781479974474

Surveillance radar network is the network of some radar station to monitor and keep watch ship/vessel traffic. The communication of these station used tcp/ip over internet and local area network. The security system is an important part that can not be ignored for network communication. This paper proposed a prototype of security system for surveillance radar network, which is handling the security of communications over the Internet between a radar station to master station. The system is designed to protect the radar data against unauthorized parties. From the previous work, there was a weakness in the pseudorandom number generator. The generated number could not satisfy the randomness, it might be raise a security problem. Thus, Pseudorandom Number Generator (PNRG) using chaos algorithm was added to strengthen the salt cryptographic scheme. The analysis of result will be discussed to obtain the advantages of new system. Finally, a layered security system has been developed by taking advantage of a variety of encryption algorithms to get the best protection for the security of surveillance radar network communication.

关键词： chaos algorithm security system surveillance radar network salt cryptography Identity Based Security(IBE)

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Application of CSK Encryption algorithm in Video Synergic Command Systems

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JOURNAL OF ORGANIZATIONAL AND END USER COMPUTING 2021年第2期34卷 1-18页

作者： Qin, Lele Zhang, Guojuan You, Li Hebei Univ Sci & Technol Sch Econ & Management Shijiazhuang Hebei Peoples R China Hebei Coll Ind & Technol Dept Ind Basic Educ Shijiazhuang Hebei Peoples R China Hebei Coll Ind & Technol Dept Econ & Trade Shijiazhuang Hebei Peoples R China

Video command and dispatch systems have become essential communication safeguard measures in circumstances of emergency rescue, epidemic prevention, and control command as data security has become especially important. After meeting the requirements of voice and video dispatch, this paper proposes an end-to-end encryption method of multimedia information that introduces a multiple protection mechanism including selective encryption and selective integrity protection. The method has a network access authentication and service encryption workflow, which implants startup authentication and key distribution into the information control signaling procedure. This method constitutes a key pool with the three-dimensional Lorenz system, the four-dimensional cellular neural network (CNN) system, and the four-dimensional Chen system where the key source system and initial conditions are decided by the plaintext video frame itself. Then, this method optimizes the chaotic sequences to further enhance system security.

关键词： chaos algorithm Encryption and Decryption Key Distribution Synergic Commands Video Conferencing Video Encryption Video Security Video Synergic Command System Video Systems

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Network traffic forecasting combination model based on wavelet transform and chaos algorithm

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INTERNATIONAL JOURNAL OF WAVELETS MULTIRESOLUTION AND INFORMATION PROCESSING 2014年第3期12卷 1450029-1450029页

作者： Dang, Xiao Chao Hao, Zhan Jun Li, Yan Lu, Zhen Yu Gao, Qi Northwest Normal Univ Coll Comp Sci & Engn Lanzhou 730070 Peoples R China Gansu IOT Res Ctr Lanzhou 730070 Peoples R China

Based on wavelet transform and chaos algorithm, this paper presents a Network Traffic Forecasting Combination Model. The model introduces chaos algorithm for training the BP network and optimizing weights so as to avoid gradient descent algorithm that slowly converges and likely obtains local optimum results. Before forecasting, we first perform wavelet decomposition on the pretreated flow. Then, we utilize the FARIMA model and the improved Elman neural network model to forecast according to approximate components and detailed components, respectively. At last, we use the combination model for the network traffic forecasting. Simulation results confirmed the improved accuracy of the model, and comparing to traditional FARIMA model and wavelet neural network (WNN) model, the model can reduce the deviation.

关键词： Wavelet transform chaos algorithm network traffic forecasting

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