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22nd International Conference on Neural Information Processing (ICONIP)

作者： Shao, Peng Wu, Zhijian Zhou, Xuanyu Zhou, Xinyu Wang, Zelin Dang Cong Tran Wuhan Univ State Key Lab Software Engn Wuhan 430072 Hubei Peoples R China Wuhan Univ Comp Sch Wuhan 430072 Hubei Peoples R China Vietnam Acad Sci & Technol Hanoi Vietnam Jiangxi Normal Univ Sch Comp & Informat Engn Nanchang 330022 Peoples R China

ISBN: (纸本)9783319265322;9783319265315

According to characteristics of rapid speed and large quantity in the process of bacterial reproduction, and natural selection, survival of the fittest in the process of evolution, the framework of bacterial reproduction optimization(BRO) algorithm is proposed from a macro perspective of bacteria reproduction. The process of bacteria reproduction is divided to four periods with lag period, logarithmic period, stable period and decline period. Likewise, the process of optimization algorithm proposed by this paper is segmented into four periods with initial period, iteration period, stable period and decline period. Based on the framework, strategies are introduced to design BRO more efficiently. Experimental results and theoretical analysis show that BRO has faster convergence speed and higher accuracy for high-dimensional problems.

关键词： intelligent algorithms Reproduction Bacterial swarm Particle swarm optimization

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Experimental Study and Modeling of Soft Body Behavior Based on the Mass-Spring-Damper Method 9

Experimental Study and Modeling of Soft Body Behavior Based ...

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9th RSI International Conference on Robotics and Mechatronics (ICRoM)

作者： Najafabadi, Alireza Maleki Khanmirza, Esmaeel Markazi, Amirhossein Davaie Iran Univ Sci & Technol Sch Mech Engn Tehran Iran

ISBN: (纸本)9781665420945

Studying and modeling soft body behavior is one of the recent topics in mechanics and biomechanics. Various methods have been proposed to model the dynamic behavior of a soft body, but among them, the mass-spring-damper (MSD) method presents the real-time behavior of the tissue. On the other hand, this method drastically reduces the computational volume and is suitable for controlling soft objects and tools in various applications such as grasping, cutting, etc. In the MSD method, the viscoelastic properties of the soft body are determined by the coefficients of the spring and the damper. Therefore, finding these coefficients is one of the critical challenges of the mass-spring-damper method. In this paper, the dynamic behavior of a sponge is investigated using the MSD method. For a more detailed study of this behavior, linear and nonlinear springs are included in the dynamic equations. Experiments were performed on the sponge to validate the model extracted from the simulation. In order to extract the experimental results, it was necessary to use image processing. Finally, intelligent evolutionary algorithms were used to find the optimal unknown coefficients.

关键词： Soft body modeling Mass-spring models Image processing intelligent algorithms

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A Space-Based Generic Pattern for Self-Initiative Load Balancing Agents

A Space-Based Generic Pattern for Self-Initiative Load Balan...

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10th International Workshop on Engineering Societies in the Agents World

作者： Kuehn, Eva Sesum-Cavic, Vesna Vienna Univ Technol Inst Comp Languages Space Based Comp Grp A-1040 Vienna Austria

ISBN: (纸本)9783642102028

Load-Balancing is a significant problem in heterogeneous distributed systems. There exist many load balancing algorithms, however, lost approaches are very problem specific oriented mid a comparison is therefore complex. This paper proposes a generic architectural pattern for a load balancing framework that allows for the plugging of different load balancing algorithms, reaching from unintelligent to intelligent ones, to ease the selection of the best algorithm for a certain problem scenario. As in complex network environments there is no "one-fits-all solution", also the integration of several different algorithms shall be supported. The presented pattern assumes autonomous agents and decentralized control. It can be composed towards arbitrary network topologies, foresees exchangeable policies for load-balancing, and uses a black-board based communication mechanism to achieve high software architecture agility. The pattern has been hnplemented and first instantiations of it with three algorithms have been bench implemented and first instantiations of it with three algorithms have been benchmarked.

关键词： Load balancing self-organization autonomous agents coordination patterns intelligent algorithms complex distributed systems

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Research of Harmony Search Algorithm based on variable metric method

Research of Harmony Search Algorithm based on variable metri...

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26th Chinese Control and Decision Conference (CCDC)

作者： Qi Wei Liu Xuwang Henan Univ Sch Business Adm Kaifeng 475004 Peoples R China

ISBN: (纸本)9781479937066

Harmony search algorithm is a good intelligent optimization algorithm, but it is not high robustness and large random. So combining variable metric method of the better local search ability, Harmony Search Algorithm based on variable metric method is proposed. Giving the theory of the basic harmony search algorithm and variable metric method, the specific processes of the improved algorithm is analyzed, through four test functions demonstrate the performance of the improved algorithm. The numerical experiments show that the means of the algorithm are better than other given algorithms in the text, and standard deviations are better than other algorithms. This shows the improved algorithm has the better optimization ability, good robustness, and the method is easy implemented, it has a good prospect in engineering.

关键词： intelligent algorithms variable metric method harmony search algorithm robustness

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Cooperative Search and Rescue with Swarm of Robots Using Binary Dragonfly Algorithm 15

Cooperative Search and Rescue with Swarm of Robots Using Bin...

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15th International Multi-Conference on Systems, Signals and Devices (SSD)

作者： Abuomar, Lina Al-Aubidy, Kasim Philadelphia Univ Intelligent & Embedded Syst Res Grp Fac Engn Irbid Jordan

ISBN: (纸本)9781538653050

This paper presents development and evaluation of an intelligent algorithm for swarm mobile robots cooperation. This algorithm can be shared between collections of robots to cooperate in order to achieve search and rescue tasks. A binary dragonfly algorithm has been modified by considering two more behaviors;obstacle avoidance and communication constrains. The implemented algorithm has been tested to check its performance in reaching the best solution and to reach an optimal solution within relatively shorter time. The performance of the robotic dragonfly algorithm has been compared with other search and rescue algorithms and the obtained results demonstrate its features in cooperation to reach a single objective.

关键词： Swarm robotic Multi-robots collaboration Optimization techniques intelligent algorithms Search and rescue

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Hands-On Convolutional Neural Networks with TensorFlow: Solve computer vision problems with modeling in TensorFlow and Python

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2018年

作者： Iffat Zafar Giounona Tzanidou Richard Burton Nimesh Patel

ISBN: (数字)9781789132823

ISBN: (纸本)9781789130331

Learn how to apply TensorFlow to a wide range of deep learning and Machine Learning problems with this practical guide on training CNNs for image classification, image recognition, object detection and many computer vision challenges. Key Features • Learn the fundamentals of Convolutional Neural Networks • Harness Python and Tensorflow to train CNNs • Build scalable deep learning models that can process millions of items Book Description Convolutional Neural Networks (CNN) are one of the most popular architectures used in computer vision apps. This book is an introduction to CNNs through solving real-world problems in deep learning while teaching you their implementation in popular Python library - TensorFlow. By the end of the book, you will be training CNNs in no time! We start with an overview of popular machine learning and deep learning models, and then get you set up with a TensorFlow development environment. This environment is the basis for implementing and training deep learning models in later chapters. Then, you will use Convolutional Neural Networks to work on problems such as image classification, object detection, and semantic segmentation. After that, you will use transfer learning to see how these models can solve other deep learning problems. You will also get a taste of implementing generative models such as autoencoders and generative adversarial networks. Later on, you will see useful tips on machine learning best practices and troubleshooting. Finally, you will learn how to apply your models on large datasets of millions of images. What you will learn • Train machine learning models with TensorFlow • Create systems that can evolve and scale during their life cycle • Use CNNs in image recognition and classification • Use TensorFlow for building deep learning models • Train popular deep learning models • Fine-tune a neural network to improve the quality of results with transfer learning • Build TensorFlow models that can scale to large da

关键词： Deep Learning Artificial Intelligence Machine Learning Python DL Frameworks Python Deep Learning algorithms Deep Learning Techniques AI Methods intelligent Programs intelligent algorithms Computational Intelligence Deep Learning for Vision

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Research Methods Review of Magnetic Materials Multi-process Coordination Production Planning and Scheduling 14

Research Methods Review of Magnetic Materials Multi-process ...

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14th International Conference on Control, Automation, Robotics and Vision (ICARCV)

作者： Liu, Yefeng Chai, Tianyou Shenyang Inst Technol Coll Informat & Control Fushun Peoples R China Northeastern Univ State Key Lab Synthet Automat Proc Ind Shenyang Peoples R China

ISBN: (纸本)9781509035496

Due to the non-renewable character, magnetic materials (especially rare earth permanent magnet) become a hot topic which world scientists are eager to explore and research. Magnetic enterprises are constantly promoting lean production. The core of lean production is production planning and scheduling, which is also the core of enterprise management. It is essential to effective control of plant inventory, improve production efficiency, reduce production cost and rise product delivery satisfaction rate. All above can be realized by using the fast and effective methods which come from multi-process coordination production planning and scheduling. A research method review of magnetic materials multi-process coordination production planning and scheduling is given on the base of describing magnetic materials production process with rare earth as the raw material. Finally, the paper gives four research fields of magnetic materials multi-process coordination production planning and scheduling.

关键词： magnetic materials(rare earth permanent magnet) NdFeB(Neodymium Iron Boron) intelligent algorithms multi-process coordination production planning and scheduling

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Ant Colony Algorithm Path Planning Based on Genetic Algorithm Fusion in 2D Grid Maps 5

Ant Colony Algorithm Path Planning Based on Genetic Algorith...

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5th International Conference on Control and Robotics (ICCR)

作者： Zhang, Yilin Zhao, Qiang Liaoning Petrochem Univ Coll Informat & Control Engn Fushun Peoples R China

ISBN: (纸本)9798350307627

In order to address the slow speed of traditional ant colony algorithms in searching for the optimal path in two-dimensional environments and the tendency to fall into local optima, this paper proposes an ant colony algorithm path planning that integrates genetic algorithms. The traditional ant colony algorithm has slow search speed and is prone to falling into local optima mainly due to the uncertainty of the initial search direction of the ant colony, as well as the difficulty in finding the global optimal solution due to the low initial pheromone concentration. Therefore, this article introduces the genetic algorithm in intelligent algorithms to improve the ant colony algorithm. By setting the parameters of the genetic algorithm and its fast search speed, it enhances the initial pheromone concentration of the ant colony algorithm, and makes a judgment on whether the path searched by the ant colony algorithm is optimal. This can lead to the result of shortening the optimal path with smaller iterations. Finally, this article conducted a simulation experiment comparison on a grid map under the same obstacle, using traditional ant colony algorithm and ant colony algorithm fused with genetic algorithm. The same starting point and endpoint were set, and the parameter values of the ant colony algorithm were fixed to meet the experimental comparison requirements. The Experiments show that the proposed algorithm has a shortest path length of 28.1253, which is 3.86% shorter than the traditional algorithm. The number of iterations is also reduced by 32.76% on the basis of the traditional algorithm, which proves that the proposed method has a good improvement effect on the traditional ant colony path planning in two-dimensional environment.

关键词： 2D environment path planning intelligent algorithms ant colony algorithm genetic algorithm

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Decentralized platforms and human relationships: How design impacts growth and collaboration automation in the tech sector

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Strategic Direction 2022年第3期38卷 9-11页

Purpose: This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies. Design/methodology/approach: This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context. Findings: This research paper concentrates on three design dimensions surrounding the formation of robust platform ecosystems like Uber and Udemy, namely: governance decentralization, shared context, and engagement. All these contribute to embedding trust and connection to a platform, by facilitating human relationships forming through them. Knowledge sharing and collaboration are core facets of building-in ever-increasing layers of innovation, and at one extreme platform governance could be completely decentralized, although this risks destabilizing the benefits of the other facets. Managers can gain plenty of commitment by involving many actors in decisions, without leaving the platform like a ship without a rudder… directionless. Originality/value: The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format. © 2021, Emerald Publishing Limited.

关键词： Autonomous organization Blockchain Decentralization Engagement intelligent algorithms Platform ecosystem

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Research on Personalized Sports Training Based on Big Data algorithms 24

Research on Personalized Sports Training Based on Big Data A...

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2024 International Conference on Smart City and Information System, ICSCIS 2024

作者： Feng, Zhibo Huang, Fei Guangxi Vocational Normal University Nanning Guangxi530007 China

ISBN: (纸本)9798400710155

This paper investigates the potential of integrating big data and AI into personalized sports training, presenting an intelligent system that analyzes user movement data for customized training plans. Utilizing machine learning and posture recognition technologies, this system offers dynamic adjustments and feedback. A 12-week experiment shows significant advantages in body composition, cardiopulmonary function, and training management over traditional methods. Highlighting a shift towards innovative training modes, the study suggests future directions for expanding research scope and application areas to enhance personalized training and national health levels through technology. © 2024 ACM.

关键词： Artificial intelligence intelligent algorithms Personalized sports training

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