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An Effective Machine Learning Approach with Hyperparameter Tuning for Sentiment Analysis

Data Intelligence 2025年第1期7卷 70-94页

作者： Saima Kanwal Ali Raza Chunyan Bai Dawei Zhang Jing Wen Dileep Kumar Engineering Research Centre of Optical Instrument and Systems Ministry of Education and Shanghai Key Lab of Modern Optical SystemUniversity of Shanghai for Science and TechnologyNo.516 Jun Gong RoadShanghai 200093China Department of Mathematics School of SciencesHebei University of TechnologyBeichen CampusTianjin 300401China Shanghai Publishing and Printing College Shanghai 200093China Zhangjiang Laboratory Shanghai 200120China Department of Electronic Engineering Faculty of EngineeringThe Islamia University of Bahawalpur63100PunjabPakistan

Sentiment analysis depends on individuals’comments and opinions on *** from social media platforms like Twitter,Quora,or Facebook poses challenges due to informal language,including acronyms,misspellings,and ambiguous ***,hyperparameters in machine learning models significantly impact *** address these issues,we propose advanced feature engineering techniques in Natural Language Processing(NLP)and hyperparameter optimization to enhance prediction accuracy and generalization *** study employs Naïve Bayes,Logistic Regression(LR),Multi-layer Perceptron(MLP),and Support Vector Machine(SVM)to classify sentiments in tweets about Elon Musk’s potential acquisition of *** dataset,consisting of 100,000 tweets,is fetched using the Twitter representational state transfer application programming interface(REST API).We outline a sentiment analysis procedure to classify unstructured Twitter data,identify influential keywords,and categorize sentiments as Positive,Negative,or *** a hybrid Lexicon NLP approach,we extract contextually significant emotionally charged words and assign sentiment *** optimization via automated search methods ensures alignment with classifier performance *** achieved an impressive accuracy rate of 97%.Cross-validation minimizes random variations,providing a reliable assessment of the model’s generalization capabilities,and demonstrating the method’s accuracy in predicting sentiments with larger new unseen standard datasets,and varying sentiment.

关键词： Hybrid lexicon Logistic regression(LR) Machine learning Natural language processing(NLP)

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An Improvised Genetic Algorithm Technique on Task Scheduling in Edge and Cloud Computing systems 15

An Improvised Genetic Algorithm Technique on Task Scheduling...

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15th International Conference on Computing Communication and Networking Technologies, ICCCNT 2024

作者： Pitty, Nagarjuna Hemalatha, N. Venkata Ramana, K. Sajitha, L.P. Ramesh Babu, P. Babu, M.Dinesh Indian Institute of Science Karnataka Bengaluru India Tamilnadu Chennai India QIS College of Engineering and Technology Department of CSE Andrapradesh Ongole India R.M.K Engineering College Department of Computer Science and Business System Tamilnadu Kavaraipettai India Wollega University College of Engineering and Technology Department of Computer Science Oromia Region Nekemte Ethiopia Rajalakshmi Institute of Technology Department of Mechanical Engineering Tamilnadu Chennai India

ISBN: (纸本)9798350370249

In current years, part cloud computing systems have received huge adoption because of their capability to provide low latency and high bandwidth offerings to users. however, one of the primary challenges in these structures is green undertaking scheduling in the presence of dynamic and heterogeneous sources. To deal with this trouble, genetic set of rules (GA) optimization strategies were proposed as a potential solution. This approach utilizes genetic operators, which include mutation and crossover, to conform a populace of potential solutions and choose the best one. by way of considering various constraints and objectives, consisting of strength consumption and make span, the GA-primarily based project scheduling technique can efficaciously optimize useful resource allocation in area cloud computing structures, at the end improving their performance and resource utilization. © 2024 IEEE.

关键词： Scheduling algorithms

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Control and Stability of Large-scale Power system with Highly Distributed Renewable Energy Generation:Viewpoints from Six Aspects

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CSEE Journal of Power and Energy systems 2023年第1期9卷 8-14页

作者： Qing-Hua Wu Anjan Bose Chanan Singh Joe H.Chow Gang Mu Yuanzhang Sun Zhaoxi Liu Zhigang Li Yang Liu School of Electric Power Engineering South China University of TechnologyGuangzhou 510640China School of Electrical Engineering&Computer Science Washington State UniversityPullmanWA 99164USA Department of Electrical and Computer Engineering Texas A&M UniversityCollege StationTX 77843USA Department of Electrical Computer and Systems EngineeringRensselaer Polytechnic Institute(RPI)TroyNYUSA Key Laboratory of Modern Power System Simulation and Control&Renewable Energy Technology Ministry of Education(Northeast Electric Power University)Jilin 132012China School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072China

Power systems are moving toward a low-carbon or carbon-neutral future where high penetration of renewables is *** conventional fossil-fueled synchronous generators in the transmission network being replaced by renewable energy generation which is highly distributed across the entire grid,new challenges are emerging to the control and stability of large-scale power *** analysis and control methods are needed for power systems to cope with the ongoing *** the CSEE JPES forum,six leading experts were invited to deliver keynote speeches,and the participating researchers and professionals had extensive exchanges and discussions on the control and stability of power ***,potential changes and challenges of power systems with high penetration of renewable energy generation were introduced and explained,and advanced control methods were proposed and analyzed for the transient stability enhancement of power grids.

关键词： Distributed energy resources high converter penetration power system control renewable energy generation stability control transient stability

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Fractional Order Differential Evolution

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IEEE Transactions on Evolutionary Computation 2024年第3期29卷 1-1页

作者： Wang, Kaiyu Gao, Shangce Zhou, MengChu Zhan, Zhi-Hui Cheng, Jiujun Faculty of Engineering University of Toyama Toyama-shi Japan Department of Electrical and Computer Engineering New Jersey Institute of Technology Newark NJ USA College of Artificial Intelligence Nankai University Tianjin China Ministry of Education Key Laboratory of Embedded System and Service Computing Tongji University Shanghai China

Differential evolution (DE) is a widely recognized method to solve complex optimization problems as shown by many researchers. Yet, non-adaptive versions of DE suffer from insufficient exploration ability and uses no historical information for its performance enhancement. This work proposes Fractional Order Differential Evolution (FODE) to enhance DE performance from two aspects. Firstly, a bi-strategy co-deployment framework is proposed. The population-based and parameter-based strategies are combined to leverage their respective advantages. Secondly, the fractional order calculus is first applied to the differential vector to enhance DE’s exploration ability by using the historical information of populations, and ensures the diversity of population in an evolutionary process. We use the 2017 IEEE Congress on Evolutionary Computation (CEC) test functions, and CEC2011 real-world problems to evaluate FODE’s performance. Its sensitivity to parameter changes is discussed and an ablation study of multi-strategies is systematically performed. Furthermore, the variations of exploration and exploitation in FODE are visualized and analyzed. Experimental results show that FODE is superior to other state-of-the-art DE variants, the winners of CEC competitions, other fractional order calculus-based algorithms, and some powerful variants of classic algorithms. IEEE

关键词： Particle swarm optimization (PSO)

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Effects of ultrasonic vibration parameters on the cutting force, chip morphology, and bone cracking in bovine cortical bone milling

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International Journal of Abrasive technology 2024年第4期12卷 293-312页

作者： Hu, Yahui Zhong, Jie He, Lingrui Lin, Yize Zhang, Zhaoxiong Zhang, Chunqiu Fu, Weihua Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering National Demonstration Center for Experimental Mechanical and Electrical Engineering Education Tianjin University of Technology Tianjin300384 China Department of General Surgery Tianjin Medical University General Hospital Tianjin300052 China

Ultrasonic vibration-assisted technology is employed in orthopaedic surgery to minimise invasive effects in bone milling. This study explored the motion characteristics of ultrasonic vibration-assisted milling (UVAM), its intermittent cutting phenomenon, and tool-bone contact and separation times, via the developed experimental platform. The UVAM and conventional milling (CM) tests were carried out on bovine cortical bones with measurement of respective cutting forces and scanning electron microscope (SEM) observation of crack initiation and propagation in the milled bones. The UVAM application improved the chip-breaking ability of the milling tool and reduced the bone-milling force by 15.90%–25.06% compared to CM. Properly adjusting ultrasonic frequency and amplitude made it possible to reduce the bone cracking effect and enhance the milled bone surface quality. Copyright © 2024 Inderscience Enterprises Ltd.

关键词： Mammals

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Analysis of node importance of satellite network based on triangular motif

Analysis of node importance of satellite network based on tr...

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2023 International Conference on Communication Network and Machine Learning, CNML 2023

作者： Pei, Zhongmin Hu, Boren Luo, Zhangkai Ding, Jie Science and Technology on Complex Electronic System Simulation Laboratory Space Engineering University Beijing101416 China Department of Electronics and Optical Engineering Space Engineering University Beijing101416 China

ISBN: (纸本)9798400716683

Motif provides a local high-order substructure angle for the analysis of network structure evolution, which is of great significance for the study of the interaction between satellite network structure and function. Taking the time scrambling null motif in steady state as a reference, the stability analysis of satellite network structure is carried out from the perspective of the local structure of the motif characteristics;define the temporal degree of satellite network, and propose a satellite network node importance analysis method based on the number of node-constructed triangle motifs, and compare the changes of motifs characteristics under the deliberate attack of temporal degree and based on triangle motifs. Simulation experiments are conducted on 46-node GPS constellations containing satellites and ground stations, and it is found that the network with higher initial triangle concentration showed higher stability. In GPS satellite network where the number of node triangle motif is positively correlated with their temporal degree, the attack strategy based on the triangle motif accelerates the attenuation of the triangle subgraph, and the node importance analysis method of the satellite network has higher accuracy. © 2023 ACM.

关键词： Satellites

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F-SIFT: Fuzzy Based Smart Intelligence Farming Techniques Using IoT Technique

F-SIFT: Fuzzy Based Smart Intelligence Farming Techniques Us...

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2024 International Conference on Advances in Data engineering and Intelligent Computing systems, ADICS 2024

作者： Thanuja, R. Kalaivani, K. Kalaiselvi, R. Valarmathi, N. Vengateshwaran, M. Sastra Deemed University Department Of Cse Kumbakonam India Vit University Department Of Database System Vellore India Arasu Engineering College Department Of Cse Kumbakonam India M.Kumarasamy College Of Engineering Department Of It Karur India Sri Krishna College Of Engineering & Technology Department Of Cse Coimbatore India

ISBN: (纸本)9798350364828

Intelligent farming plays an important role in the agricultural field. Agriculture is heavily impacted by changes in the global climate, including temperature, rainfall patterns, Soil degradation, pests, and diseases that can cause significant damage to crops, leading to crop loss and reduced yields. To increase the crop yield, the proposed technique of implementing real-time prediction of crop yield IOT monitoring system called Digital Intelligence Farming Techniques (DIFT) uses a Fuzzy Inference system (FIS) to make decisions effectively and efficiently through the mobile application. Based on the real-time implementation, performance metrics like Soil moisture level, rainfall, temperature, and humidity are analyzed, and experiments are being done in the Tomato Plant. The real-time experiments were conducted in the Agriculture fields of Kumbakonam, Tamil Nadu, India. The DIFT approach will help the farmer to predict the most suitable crop to grow in that environment. © 2024 IEEE.

关键词： Soil moisture

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Resilience assessment framework toward interdependent bus-rail transit network:Structure,critical components,and coupling mechanism

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Communications in Transportation Research 2023年第1期3卷 118-129页

作者： Bing Liu Xiaoyue Liu Yang Yang Xi Chen Xiaolei Ma School of Transportation Science and Engineering Beihang UniversityBeijing100191China Department of Civil&Environmental Engineering University of UtahSalt Lake CityUT84112USA School of Computer Science and Engineering Beihang UniversityBeijing100191China Key Laboratory of Intelligent Transportation Technology and System Ministry of EducationBeijing100191China

Understanding the interdependent nature of multimodal public transit networks(PTNs)is vital for ensuring the resilience and robustness of transportation ***,previous studies have predominantly focused on assessing the vulnerability and characteristics of single-mode PTNs,neglecting the impacts of heterogeneous disturbances and shifts in travel behavior within multimodal ***,this study introduces a novel resilience assessment framework that comprehensively analyzes the coupling mechanism,structural and functional characteristics of bus-rail transit networks(BRTNs).In this framework,a network performance metric is proposed by considering the passengers’travel behaviors under various ***,stations and subnetworks are classified using the k-means algorithm and resilience metric by simulating various disturbances occurring at each station or *** proposed framework is validated via a case study of a BRTN in Beijing,*** indicate that the rail transit network(RTN)plays a crucial role in maintaining network function and resisting external disturbances in the interdependent ***,the coupling interactions between the RTN and bus transit network(BTN)exhibit distinct characteristics under infrastructure component disruption and functional *** findings provide valuable insights into emergency management for PTNs and understanding the coupling relationship between BTN and RTN.

关键词： Complex network Bus-rail transit network Resilience analysis Interdependent coupling relationship Classification analysis

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A robust multi-objective optimization algorithm for accurate parameter estimation for solar cell models

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Soft Computing 2024年第19期28卷 11265-11277页

作者： Singla, Manish Kumar Gupta, Jyoti Alsharif, Mohammed H. Kim, Mun-Kyeom Aljaidi, Mohammad Safaraliev, Murodbek Department of Interdisciplinary Courses in Engineering Chitkara University Institute of Engineering & ampTechnology Chitkara University Punjab India Applied Science Research Center Applied Science Private University Amman11931 Jordan School of Engineering and Technology K. R. Mangalam University Gurgaon Haryana122003 India Department of Electrical Engineering College of Electronics and Information Engineering Sejong University 209 Neungdong-Ro Gwangjin-Gu Seoul05006 Korea Republic of School of Energy System Engineering Chung-Ang University 84 Heukseok-Ro Dongjak-Gu Seoul06974 Korea Republic of Department of Computer Science Zarqa University Zarqa13110 Jordan Department of Automated Electrical Systems Ural Federal University Yekaterinburg620002 Russia

The accuracy of solar cell models is crucial for enhancing the performance of solar photovoltaic (PV) systems. However, existing solar cell models lack precise parameters, and the manufacturer's datasheet does not provide the required information for reliable modeling. Consequently, accurate parameter estimation becomes necessary. This paper presents a simple multi-objective optimization algorithm (Hybrid Particle Swarm Optimization and Rat Search Algorithm (PSORSA)) designed to estimate cell parameters based on this observation. Unlike other optimization algorithms addressing this issue, the proposed algorithm aims to overcome challenges related to local minima and premature convergence, which often lead to suboptimal results. The paper focuses on assessing the reliability of the proposed algorithm by comparing its performance with other well-known optimization algorithms. The proposed optimizing algorithm is tested on the CEC 2019 benchmark function. Experimental results (RMSE), including statistical analysis, validate the algorithm's effectiveness by comparing them with other algorithms. At the end, non-parametric test is performed to justify the outcomes, vouching for the better performance of the proposed algorithm. The findings demonstrate that the proposed algorithms are particularly well-suited for estimating solar PV models. With its simple structure and high accuracy, the proposed algorithm exhibits great potential for various applications in the field of solar energy. Moreover, its computational efficiency and ease of implementation further contribute to its practicality. © The Author(s) 2024.

关键词： Solar cells

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Compression behavior of nanoparticle powder considering fractal aggregate for additive manufacturing

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Ceramics International 2024年第14期50卷 26140-26148页

作者： Huang, Congliang Hu, Zeli Wang, Yibo Hsu, Shu-Han Wang, Xiaodong State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources North China Electric Power University Beijing102206 China Research Center of Engineering Thermophysics North China Electric Power University Beijing102206 China School of Low-carbon Energy and Power Engineering China University of Mining and Technology Xuzhou221116 China Department of Mechanical Engineering National Taipei University of Technology Taipei10608 Taiwan

Compression behavior of nanoparticle powder is still unclear, while it could largely affect its applications in additive manufacturing. Considering the fractal structure of aggregates in nanoparticle powder, from the van der Waal's state equation, the relation between porosity and compression pressure of nanoparticle powder was modeled theoretically, i.e. (P + c)(φ-a)=(1-a)c, here P is pressure, φ is porosity, a and c are parameters defined in main text. The model could capture the compression behavior of nanoparticle powders well. Under the same compression pressure, smaller nanoparticles will lead to larger porosity and thus lower thermal conductivity of nanoparticle packed beds, due to the easier aggregate of smaller nanoparticles. The compression behavior and the thermal conductivity of nanoparticle powders or packed beds are expected to supply information for powder spreading and sintering treatment respectively in additive manufacturing. © 2024 Elsevier Ltd and Techna Group S.r.l.

关键词： Nanoparticles

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