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2nd International Conference on Intelligent Systems Design and Engineering Applications, ISDEA 2023

作者： Jia, Li Xu, Ding Shuang, Guo School of Information and Control Engineering Jilin Institute of Chemical Technology Jilin132022 China School of Computer Science Northeast Electric Power University Jilin132012 China Science and Technology Institute of Jilin City Jilin132022 China

ISBN: (纸本)9789819963027

This paper proposes the development strategy for Intelligent manufacturing transformation, with the help of both SWOT analysis and AHP analysis, in the case of focusing on the Jilin city Automobile Industry. Firstly found the influence factors of Jilin city automobile industry’s intelligent manufacturing transformation, based on SWOT analysis. Secondly, the AHP quantitative analysis model is constructed, and the Delphi survey method is used for quantitative calculation that had been taken Consistency checking results. Then determine the strategic quadrilateral, to obtain the development strategy azimuth and strategic strength. The strategic positioning and trend of the intelligent transformation and development of the automobile industry in Jilin City are determined, and the implementation countermeasures of the development strategy are formulated. © 2024, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Automotive industry

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The Use of Both Temperature Field and Heat Fluxes to Identify the Thermal Conductivity and Volumetric Heat Capacity 15th

The Use of Both Temperature Field and Heat Fluxes to Iden...

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15th International Conference on Optimization and Applications, OPTIMA 2024

作者： Zubov, Vladimir Gorchakov, Andrei Federal Research Center "Computer Science and Control" of the Russian Academy of Sciences Moscow Russia Moscow Institute of Physics and Technology Institutskii per. 9 Dolgoprudny141701 Russia

ISBN: (纸本)9783031791185

The study of nonlinear problems associated with the process of heat transfer in material is very important for practice. Previously, the authors proposed an effective algorithm for determining the volumetric heat capacity and thermal conductivity of a substance based on the results of experimental observations of the dynamics of the temperature field in an object or the dynamics of heat flows at the boundary of the domain. In this work, a new cost functional is used to determine temperature-dependent thermodynamic parameters, which is a weighted sum of the deviation of temperature in the domain and heat fluxes at the boundary of the domain from the experimental values. The use of the new functional showed a noticeable increase in the efficiency of the proposed algorithm and the reliability of the results obtained. The consideration is carried out on the basis of the first boundary value problem for a one-dimensional non-stationary heat equation. The inverse coefficient problem under consideration is reduced to a variational problem, which is solved by gradient methods based on the application of the Fast Automatic Differentiation technique. The question of the uniqueness of the solution to the inverse problem is investigated. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Cost functions

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SensoryT5: Infusing Sensorimotor Norms into T5 for Enhanced Fine-grained Emotion Classification 8

SensoryT5: Infusing Sensorimotor Norms into T5 for Enhanced ...

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8th Workshop on Cognitive Aspects of the Lexicon, CogALex 2024

作者： Xia, Yuhan Zhao, Qingqing Long, Yunfei Xu, Ge Wang, Jia School of Computer Science and Electronic Engineering University of Essex United Kingdom Institute of Linguistics Chinese Academy of Social Sciences China College of Computer and Control Engineering Minjiang University China Department of Intelligent Science Xi’an Jiaotong-Liverpool University China

ISBN: (纸本)9782493814456

In traditional research approaches, sensory perception and emotion classification have traditionally been considered separate domains. Yet, the significant influence of sensory experiences on emotional responses is undeniable. The natural language processing (NLP) community has often missed the opportunity to merge sensory knowledge with emotion classification. To address this gap, we propose SensoryT5, a neuro-cognitive approach that integrates sensory information into the T5 (Text-to-Text Transfer Transformer) model, designed specifically for fine-grained emotion classification. This methodology incorporates sensory cues into the T5’s attention mechanism, enabling a harmonious balance between contextual understanding and sensory awareness. The resulting model amplifies the richness of emotional representations. In rigorous tests across various detailed emotion classification datasets, SensoryT5 showcases improved performance, surpassing both the foundational T5 model and current state-of-the-art works. Notably, SensoryT5’s success signifies a pivotal change in the NLP domain, highlighting the potential influence of neuro-cognitive data in refining machine learning models’ emotional sensitivity. © 2024 ELRA Language Resource Association.

关键词： Classification (of information)

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Modeling and Optimization of controlled Conveyor Systems Using Intelligent controllers 15th

Modeling and Optimization of Controlled Conveyor Systems U...

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15th International Conference on Optimization and Applications, OPTIMA 2024

作者： Petrov, Alexey Druzhinina, Olga Masina, Olga Bunin Yelets State University Yelets Russia Federal Research Center "Computer Science and Control" of Russian Academy of Sciences Moscow Russia V. A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences Moscow Russia

ISBN: (纸本)9783031791185

The construction of generalized mathematical models is proposed that describe the dynamics of a controlled belt conveyor with a variable angle between the horizontal plane and the plane of the belt. The models under consideration are defined using nonlinear nonstationary systems of four differential equations with switching. Switching modes are characterized by a change in the loading and unloading sequence. Statements of optimal control problems are presented under restrictions on the magnitude of control and on the speed of control. Synthesis of neural network controllers for stabilization of the angular position of the conveyor is carried out. controllers are synthesized using such direct propagation neural networks for which reinforcement learning is implemented based on the optimization algorithm of differential evolution. A comparative analysis of the effectiveness of synthesized controllers is carried out. Algorithmic support for modeling controlled conveyor systems is developed using intelligent analysis and global parametric optimization methods. The results of computational experiments are presented. The obtained results can find application in solving problems of optimal stabilization of dynamic systems with switching. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Belt conveyors

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Wind Power Prediction Based on Machine Learning and Deep Learning Models

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computers, Materials & Continua 2023年第1期74卷 715-732页

作者： Zahraa Tarek Mahmoud Y.Shams Ahmed M.Elshewey El-Sayed M.El-kenawy Abdelhameed Ibrahim Abdelaziz A.Abdelhamid Mohamed A.El-dosuky Faculty of Computers and Information Computer Science DepartmentMansoura UniversityMansoura35561Egypt Faculty of Artificial Intelligence Kafrelsheikh UniversityKafrelsheikh33511Egypt Faculty of Computers and Information Computer Science DepartmentSuez UniversitySuezEgypt Department of Communications and Electronics Delta Higher Institute of Engineering and TechnologyMansoura35111Egypt Faculty of Artificial Intelligence Delta University for Science and TechnologyMansoura35712Egypt Computer Engineering and Control Systems Department Faculty of EngineeringMansoura UniversityMansoura35516Egypt Department of Computer Science Faculty of Computer and Information SciencesAin Shams UniversityCairo11566Egypt Department of Computer Science College of Computing and Information TechnologyShaqra University11961Saudi Arabia Department of Computer Science Arab East CollegesRiyadh13544Saudi Arabia

Wind power is one of the sustainable ways to generate renewable *** recent years,some countries have set renewables to meet future energy needs,with the primary goal of reducing emissions and promoting sustainable growth,primarily the use of wind and solar *** achieve the prediction of wind power generation,several deep and machine learning models are constructed in this article as base *** regression models are Deep neural network(DNN),k-nearest neighbor(KNN)regressor,long short-term memory(LSTM),averaging model,random forest(RF)regressor,bagging regressor,and gradient boosting(GB)*** addition,data cleaning and data preprocessing were performed to the *** dataset used in this study includes 4 features and 50530 *** accurately predict the wind power values,we propose in this paper a new optimization technique based on stochastic fractal search and particle swarm optimization(SFSPSO)to optimize the parameters of LSTM *** evaluation criteria were utilized to estimate the efficiency of the regression models,namely,mean absolute error(MAE),Nash Sutcliffe Efficiency(NSE),mean square error(MSE),coefficient of determination(R2),root mean squared error(RMSE).The experimental results illustrated that the proposed optimization of LSTM using SFS-PSO model achieved the best results with R2 equals 99.99%in predicting the wind power values.

关键词： Prediction of wind power data preprocessing performance evaluation

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Scientific Research Transformation Needed for Comprehensive Artificial Intelligence Implementation 17

Scientific Research Transformation Needed for Comprehensive ...

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17th International Conference on Management of Large-Scale System Development, MLSD 2024

作者： Medennikov, Viktor Bogatyreva, Larisa Federal Research Center 'Computer Science and Control' of the Russian Academy of Sciences Information and Computing Systems Department Moscow Russia V.A. Trapeznikov Institute of Control Sciences of the Russian Academy of Sciences Laboratory of Modular Data Processing and Control Systems Moscow Russia

ISBN: (纸本)9798350375718

The paper deals with complementary changes in scientific research and real economy (exemplified by the farming industry) taking place when using the holistic approach to the industry's digital transformation resulting in the appearance of precise agrarian technologies that require a comprehensive, system-based combination of research and production resources that are able to ensure increased productivity in the industry. We demonstrate that among these new technologies, the artificial intelligence methods have a special significance. They have to, however, go through integration transformations to become standards for the proposed common digital farming management platform. © 2024 IEEE.

关键词： Agricultural economics

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Unveiling drug-induced side effects through network-based analysis: An update

Unveiling drug-induced side effects through network-based an...

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2024 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2024

作者： Funari, Alessio Conte, Federica Paci, Paola Sapienza University of Rome Institute for Systems Analysis and Computer Science 'Antonio Ruberti' National Research Council Department of Translational and Precision Medicine Rome Italy National Research Council Institute for Systems Analysis and Computer Science 'Antonio Ruberti' Rome Italy Sapienza University of Rome Department of Computer Control and Management Engineering Rome17177 Italy

ISBN: (纸本)9798350386226

In this article, we propose an updated version of our previously developed model for predicting drug-side effect associations, applied to two case studies: long QT syndrome and asthma. The classifier accepts the name of a specific drug side effect as input and outputs a list of drugs potentially associated with this side effect. By simulating how drug effects propagate within the interactome using the Random Walk with Restart algorithm, the classifier identifies genes potentially associated with the onset of the side effect. Based on the rationale that the more a drug perturbs these genes, the more likely it is to cause the side effect, the model identifies drugs potentially linked to the onset of the side effect. Moreover, the model enables the categorization of drugs into chemical subclasses using the ClassyFire schema, facilitating the analysis of complex side effects, such as asthma, through more specific mechanisms. The results show that the model identifies both drugs known to be associated with certain side effects, as well as drugs not officially reported by the FDA, demonstrating its generalizability and practical relevance. This method is also adaptable for analyzing other side effects. © 2024 IEEE.

关键词： drug side effect network medicine random walk

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Interaction model estimation-based robotic force-position coordinated optimization for rigid-soft heterogeneous contact tasks

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Biomimetic Intelligence & Robotics 2025年第1期5卷 77-86页

作者： Haochen Zheng Xueqian Zhai Hongmin Wu Jia Pan Zhihao Xu Xuefeng Zhou Institute of Intelligent Manufacturing Guangdong Academy of SciencesGuangdong Key Laboratory of Modern Control TechnologyGuangzhou 510070China School of Rail Transportation Wuyi UniversityJiangmen 529020China Department of Computer Science The University of Hong KongHong Kong 999077China

Inspired by Model Predictive Interaction control(MPIC),this paper proposes differential models for estimating contact geometric parameters and normal-friction forces and formulates an optimal control problem with multiple constraints to allow robots to perform rigid-soft heterogeneous contact *** the MPIC,robot dynamics are linearized,and Extended Kalman Filters are used for the online estimation of geometry-aware ***,a geometry-aware Hertz contact model is introduced for the online estimation of contact *** then implement the force-position coordinate optimization by incorporating the contact parameters and interaction force constraints into a gradient-based optimization *** validations were designed for two contact modes:“single-point contact”and“continuous contact”,involving materials with four different Young’s moduli and tested in human arm“relaxation-contraction”*** indicate that our framework ensures consistent geometry-aware parameter estimation and maintains reliable force interaction to guarantee *** method reduces the maximum impact force by 50%and decreases the average force error by 42%.The proposed framework has potential applications in medical and industrial tasks involving the manipulation of rigid,soft,and deformable objects.

关键词： Heterogeneous contact Interaction model estimation Coordination optimization Model Predictive control

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An Online Unsupervised Streaming Features Selection Through Dynamic Feature Clustering

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2023年第5期4卷 1281-1292页

作者： Yan, Xuyang Homaifar, Abdollah Sarkar, Mrinmoy Lartey, Benjamin Gupta, Kishor Datta North Carolina a&t State University Autonomous Control and Information Institute GreensboroNC27411 United States Computer Science Department Clark Atlanta University AtlantaGA30314 United States

Streaming feature selection (SFS) is emerging as a key research direction that addresses the nonstationary property of feature streams when the sample size is fixed. Most existing SFS techniques are supervised methods and ignore the label scarcity. Real-world datasets are typically unlabeled and the labeling costs are expensive. Although some unsupervised SFS approaches are proposed, these approaches are either limited to the homogeneous feature types or require substantial computational complexity. To address these problems, we propose an online unsupervised feature selection framework using dynamic feature clustering in this article. We derived a recursive density lower bound to estimate the density distribution of feature streams and developed a density-based dynamic clustering method to perform the online feature stream clustering for exploring feature redundancy. An unsupervised online feature relevance maximization and redundancy minimization strategy is introduced to extract a subset of important features with low redundancy from the feature stream. Experimental results on 13 well-known benchmark datasets and comparison studies with 7 state-of-the-art supervised SFS methods demonstrate that the proposed unsupervised method provides statistically comparable performance with the supervised SFS techniques while the label information is unknown. © 2020 IEEE.

关键词： Redundancy

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Motion planning for robotics:A review for sampling-based planners

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Biomimetic Intelligence & Robotics 2025年第1期5卷 15-34页

作者： Liding Zhang Kuanqi Cai Zewei Sun Zhenshan Bing Chaoqun Wang Luis Figueredo Sami Haddadin Alois Knoll School of Computation Information and Technology(CIT)Technical University of MunichMunich 85748Germany Munich Institute of Robotics and Machine Intelligence(MIRMI) Technical University of MunichMunich 80992Germany School of Control Science and Engineering Shandong UniversityJinan 250061China School of Computer Science University of NottinghamNottingham 315199United Kingdom

Recent advancements in robotics have transformed industries such as manufacturing,logistics,surgery,and planetary exploration.A key challenge is developing efficient motion planning algorithms that allow robots to navigate complex environments while avoiding collisions and optimizing metrics like path length,sweep area,execution time,and energy *** the available algorithms,sampling-based methods have gained the most traction in both research and industry due to their ability to handle complex environments,explore free space,and offer probabilistic completeness along with other formal *** their widespread application,significant challenges still *** advance future planning algorithms,it is essential to review the current state-of-the-art solutions and their *** this context,this work aims to shed light on these challenges and assess the development and applicability of sampling-based ***,we aim to provide an in-depth analysis of the design and evaluation of ten of the most popular planners across various *** findings highlight the strides made in sampling-based methods while underscoring persistent *** work offers an overview of the important ongoing research in robotic motion planning.

关键词： Robotics Motion planning Sampling-based algorithms

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