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An Improved Adaptive Genetic Algorithm for Robot Path Planning

An Improved Adaptive Genetic Algorithm for Robot Path Planni...

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Electrical engineering and Control science (IC2ECS), international conference on

作者： Yimin Xiao Mingming Zhao School of Information Engineering Ezhou University Ezhou China

To solve the problems of slow convergence speed and easy to fall into local optimum when adaptive genetic algorithm is applied to robot path planning, an improved adaptive genetic path planning method is proposed. In this method, turning angle evaluation index is introduced to improve the practicability of the path planning objective function; The adaptive adjustment strategy for optimizing the crossover probability and mutation probability, and the disaster operation and reversal operation are added, effectively improving the global optimization ability and convergence speed of path planning. The simulation results show that compared with the traditional adaptive genetic algorithm, this algorithm has stronger global optimization ability, requires fewer iterations, and its path planning performance is better than other improved algorithms.

关键词： Simulation Genetics Turning Linear programming Path planning Indexes Robots

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Optimizing rice distribution routes in Indonesia using a two-step linear programming considering logistics costs 2

Optimizing rice distribution routes in Indonesia using a two...

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2nd international conference on sciences and Technology Applications, ICOSTA 2020

作者： Nurprihatin, Filscha Regina, Tasya Rembulan, Glisina Dwinoor Department of Industrial Engineering Faculty of Technology and Design Universitas Bunda Mulia Jakarta Indonesia

The increase in rice consumption should be balanced with an increase in rice production. However, although the national rice production was declared a surplus, the volume of national rice imports also increased. The imports in 2018 were 2.2 million tons and showed that surplus rice production is not effectively taken as an advantage in overcoming the deficit in some provinces in Indonesia. Some provinces that experiencing surplus should be able to fill the shortage in the other provinces. This paper contributes to determine distribution routes and help the government to fulfill the shortage demand. This study uses the two-steps linear programming method. The first step is performed by the transportation model and followed by the Capacitated Vehicle Routing Problem (CVRP) model in sequence. This two-step linear programming reaches an optimal global solution in distributing goods from oversupply provinces to the over-demand one. The results show cost savings are gained if this strategy is performed to meet the demand, rather than importing the rice. © Published under licence by IOP Publishing Ltd.

关键词： Linear programming

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Three-Dimensional Path Planning for Unmanned Aerial Vehicles Based on Multi-Strategy Improved Spider Wasp Optimization 2

Three-Dimensional Path Planning for Unmanned Aerial Vehicles...

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2nd international conference on the Frontiers of Intelligent Control, Measurement, and Signal Systems, FICMSS 2025

作者： Hu, Yanan Peng, Zhenni Yang, Xintong Ling, Zhicheng College of Electronic Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing210016 China Fundamental Experimental Teaching Department Nanjing University of Aeronautics and Astronautics Nanjing210016 China

Aiming at the issues of slow search speed, limited local search capability and easy to become trapped in local optimum of Spider Wasp Optimization (SWO) in the trajectory planning algorithm of Unmanned Aerial Vehicles (UAVs), this paper proposes an Improved Spider Wasp Optimization (ISWO).The initialization of the population in the ISWO algorithm using chaotic mapping techniques enhances uniformity and diversity of initial solutions, preventing premature convergence and facilitating thorough exploration of the search space. This unpredictability helps avoid local optima traps. Additionally, the adaptive weight factor adjusts the equilibrium between exploration and exploitation founded on the optimization state, allowing efficient transitions between broad and focused searches. The Cauchy variant optimization enables larger jumps in the search space, aiding in escaping local optima and exploring distant areas for better solutions. Together, these improvements lead to faster convergence, reduced planning time, and better solution quality in complex optimization problems. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Mathematical programming

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Research on Supply Chain Integrated Planning Model Based on Analytic Hierarchy Process and Optimization Theory 2

Research on Supply Chain Integrated Planning Model Based on ...

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2nd international conference on Computer science and Management Technology, ICCSMT 2021

作者： Jiang, Mingxuan School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China

ISBN: (纸本)9781665420631

By analyzing the previous order quantity, supplier's supply quantity and transshipment homeopathy quantity, this paper designed the ordering scheme of raw materials for a building and decoration board manufacturer, and considered the transportation of raw materials. First of all, this paper finds four factors that affect suppliers: total supply quantity, supply times, supply satisfaction rate and average supply completion rate, determines the coefficient by AHP, and considers scoring, and selects 50 most important suppliers. Next, select the important suppliers from top to bottom, and order their historical maximum supply every week until the maximum production capacity is met. According to the order price, give priority to a and c, and reduce b. Finally, select materials with low loss and high transportation yield. Finally, the number of selected enterprises is increased, and the most Class A materials and the least Class C materials are purchased, so as to maximize the production capacity and minimize the losses while ensuring that one supplier is transported by only one forwarder. © 2021 IEEE.

关键词： Linear programming

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Linear programming in Market Management Using artificial Intelligence 2nd

Linear Programming in Market Management Using Artificial Int...

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2nd international conference on Mechanical engineering Design, ICMechD 2019

作者： Uday, Shetty Vignesh Hamritha Chaudhary, Gaurav Department of Industrial Engineering and Management Ramaiah Institute of Technology Bangalore560054 India Department of Electronics and Communication Engineering Ramaiah Institute of Technology Bangalore560054 India

ISBN: (纸本)9789811547447

The intelligence exhibited by machines in decision making using mathematical algorithms in contrast to the human intelligence is known as artificial intelligence (AI). It is an area of engineering science that focuses on the modeling of intelligent systems that work and act in response like humans. The tasks that AI includes are face recognition, voice recognition, planning, learning, and predicting. Linear programming problem (LPP) is a tool to solve the real-life problems using the standard mathematical approach that gives us the optimal solution. This paper aims at providing the investors an aid in decision making while advertising their business with combination of the tools that are available. Neural network model will be formulated and trained on the basis of dataset that includes past data of variables such as amount of investment, type of business, demographical area, and consumer attributes. The output nodes include the variables based on the type of advertisement. After training and testing are finished, user provides the model with the inputs and the output predicts the optimal percentage of marketing of product in different fields. This way the model will help us to make sound decisions in allocating the total investment among the variables. © 2021, Springer Nature Singapore Pte Ltd.

关键词： artificial intelligence Linear programming problem Marketing Productivity

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Design of Control System for Rotating LED Display Based on Single Chip Microcomputer

Design of Control System for Rotating LED Display Based on S...

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Electrical engineering and Control science (IC2ECS), international conference on

作者： Jieshi Luo Liang Zhou Hongyi Wu Jinliang Luo Department of Mechanical Engineering University of South China Hengyang China

Modern Light Emitting Diode(LED) display screen has a wide range of applications, but its structure is simple and lacks creativity. At present, LED screens are powered by rotating parts and batteries, so the battery capacity is rather small and cannot work continuously. Thus, a method which can effectively use resources, reduce cost and make up for the shortage of rectangular display screen is required. In terms of software, keiluvision5 development platform and Combined programming Language are used to design it into a reasonable programming algorithm and download it to MCU minimization system to realize the control of the whole display. In terms of technology, based on the deep understanding of LED rotary display technology, this paper uses STC12C5A32S2 single chip microcomputer as the control center, and connects the components in series; The precise display of date and time is realized through DS1302, which enhances the practicability; The constant rotation speed is realized through the infrared diode, which is combined with the program to ensure that the normal text and image can be displayed; Use the welding of Printed Circuit Board(PCB) to make the production more efficient; Using wireless power supply can not only work continuously, but also prolong the service life of the system.

关键词： Wireless communication Computer languages Costs Power supplies Welding Production Microcomputers

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Smart IoT_Cloud-Based ML Technique to Classify Breast Cancer

Smart IoT_Cloud-Based ML Technique to Classify Breast Cancer

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Ambient Intelligence in Health Care (ICAIHC), international conference on

作者： Sashikanta Prusty Sujit Kumar Dash Sushree Gayatri Priyadarsini Prusty Sasanka Sekhar Dalai Nrusingha Tripathy Subrat Kumar Nayak Department of Computer Science & Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar India Department of Electrical & Electronics Engineering Siksha ‘O’ Anusandhan (Deemed to be University) Bhubaneswar India

IoT and cloud computing have a significant impact on healthcare services, particularly when it comes to disease prediction in smart cities. Big data about breast cancer (BC) can be sent through IoT devices (digital sensors, etc.) and stored in the cloud. As a result, these huge data are used to improve BC prediction accuracy in a cloud setting. Thus, BC-based cloud IoT is thought to be a significant issue that smart city stakeholders in health care must deal with. In smart cities, cloud computing helps patients predict the presence of BC anywhere and at any time by using advanced machine learning (ML) techniques. The main goal of this study is to demonstrate the effectiveness of a secure Internet of Things and cloud computing in the identification of BC at our home. Thus, we proposed an ICM (IoT_Cloud-based ML) method that describes the workflow of how a user can predict BC disease at any place and at any time. And finally, we designed performance metrics for all three models and found logistic regression model (LR) outperforms with higher accuracy of 83% than DT at 72% and NB at 80%. However, all these experiments have been carried out using Python 3.8.3 programming software on the Jupyter 6.4.3 Notebook platform in Windows 10 operating system.

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Application of LSTM in Quantitative Trading with Big Data

Application of LSTM in Quantitative Trading with Big Data

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Big Data, Information and Computer Network (BDICN), international conference on

作者： Jieyi Wang Yixuan Hu Yelin Zhao School of Computer Engineering and Science Shanghai University NO.99 Shangda Road Shanghai China. College of Sciences Shanghai University NO.99 Shangda Road Shanghai city China

Recently, the global market returns are characterized by year-long episodes of high volatility, leading market traders to struggle to maximize their total return with high-frequency trading. However, in the meantime, some classical financial characteristics have striking similarities. Therefore, an increasing amount of investors are dedicated to finding and making the most of reasonable models with computer science and machine learning, in quest of a general pattern. Accordingly, we developed a comprehensive model to help some traders with optimal transaction decisions. Given that the portfolio of cash, bitcoin and gold is gradually becoming a new choice for high returns, we chose these assets as examples to build a model to forecast the closing prices of bitcoin and gold for the next trading day based on their past stream up to today with LSTM (LongShort Term Memory) Neural Network Model. To achieve the maximum return, we used the Mean-variance Model to set the investment ratio of bitcoin and gold as variables for mathematical programming and solved the multivariate equations to find the optimal portfolio. The investment weights for each trade were obtained by comparing the lowest risk portfolio and the optimal return portfolio, i.e., the minimum variance and maximum Sharpe ratio scenarios. Finally, we evaluated our strategy through quantitative strategy indices and proved its outstanding performance.

关键词： Gold Costs Biological system modeling Computational modeling Bitcoin Predictive models Data models

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Text Steganography in Images Using Turbo Code-Walsh Code Transforms

Text Steganography in Images Using Turbo Code-Walsh Code Tra...

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Advances in engineering science and Technology (AEST), international conference on

作者： Rafal Fadhil Jabbar Osama Qasim Jumah Al-Thahab College of Engineering University of Babylon Babil Iraq

Numerous methods, such as integration between steganography and cryptography, have been suggested to protect the privacy of information exchanged. Steganography systems have come to be recognized as a crucial method for enhancing information security by using multimedia to cover up sensitive information which includes information that is invisible to the human eye. In this paper, text was concealed within a digital image using Turbo code and Walsh-code algorithm, in order to result an electronic lung x-ray containing the diagnosis of the condition embedded inside the image. The algorithm was implemented using the MATLAB programming language. The new way is exposed to multi-image noise like Gaussian, slot and paper noise, and it is found that the proposed algorithm has PSNR, BER, RMS, MSE results for Gaussian equal to 84.871, 0.0003, 0.0525, and 0.0027 respectively. These results are considered very suitable as compared to no attack.

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Intelligent PLC Code Generation in HCPS 2.0: A Multi-dimensional Taxonomy and Evolutionary Framework 25

Intelligent PLC Code Generation in HCPS 2.0: A Multi-dimensi...

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Proceedings of the 2025 2nd international conference on Generative artificial Intelligence and Information Security

作者： Weiyi Xia Yinggang Zhang Ben Zhao Wei Liu Linjie Han Qifu Ye National Engineering Research Center for Manufacturing Automation Beijing China China Academy of Machinery Science & Technology Beijing China Aerospace Long March Rocket Technology Co. LTD Beijing China

ISBN: (纸本)9798400713453

The manufacturing industry is accelerating towards the New-Generation Intelligent Manufacturing, where the automatic generation of Programmable Logic Controllers (PLCs) code serves as a key technology, crucial for enhancing the intelligence and efficiency of manufacturing systems. Traditional manual programming has become increasingly inadequate to meet the demands for flexibility and real-time performance in intelligent manufacturing. This paper reviews the integration of intelligent manufacturing and PLC technologies, highlighting the core role of Human-Cyber-Physical Systems (HCPS) and demonstrating how it effectively guides theoretical research and engineering practices in new-generation intelligent manufacturing. We innovatively classify automatic PLC code generation methods through multiple dimensions and propose a new framework for Structured Text (ST) code generation. Finally, this paper discusses future trends in controller code generation, identifying multimodal-driven intelligent generation, adaptive learning and real-time optimization, and cloud-edge collaborative intelligent generation as significant directions, forming a technical roadmap of "parallel promotion and integrated development" to support comprehensive intelligent transformation and upgrading of manufacturing.

关键词： Code generation

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