Social opinions prediction utilizes fusing dynamics equation with LLM-based agents by Junchi Yao, Hongjie Zhang, Jie Ou, Dingyi Zuo, Zheng Yang, Zhicheng Dong

“…Abstract In the context where social media emerges as a pivotal platform for social movements and shaping public opinion, accurately simulating and predicting the dynamics of user opinions is of significant importance. …”
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Prediction of cardiovascular risk using machine-learning methods. Sex-specific differences by Sara Castel-Feced, Sara Castel-Feced, Sara Castel-Feced, Sara Castel-Feced, Isabel Aguilar-Palacio, Isabel Aguilar-Palacio, Isabel Aguilar-Palacio, Isabel Aguilar-Palacio, Sara Malo, Sara Malo, Sara Malo, Sara Malo, Juan González-García, Lina Maldonado, Lina Maldonado, Lina Maldonado, María José Rabanaque-Hernández, María José Rabanaque-Hernández, María José Rabanaque-Hernández, María José Rabanaque-Hernández

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Long-term prediction for VBR video traffic based on wavelet packet decomposition by CHEN Jian1, WEN Ying-you1, ZHAO Da-zhe1, LIU Ji-ren1

“…Long-term prediction is one of the most difficult problems in the area of VBR video traffic prediction.As to the time variation,non-linearity and long range dependence in VBR video traffic trace,a novel method of feature based on multi-scale decomposition was proposed.On the analysis of the time-frequency distribution characteristics of the video trace,the wavelet packets which have the trait of arbitrary distinction and decomposition are selected.After space partition of wavelet packets,the best wavelet packet basis for feature extraction is picked out.Based on the best basis,it can do fast arbitrary multi-scale WPT（wavelet packet transform）,and obtain each higher dimension wavelet coefficients matrix.And then wavelet coefficients prediction is proposed based on LS-SVM and LMS algorithms.The long-term pre-diction of VBR video traffic is obtained through reverse wavelet transforms on the predicted wavelet coefficients.Nu-merical and simulation results are provided to validate the claims.…”
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Does machine learning outperform logistic regression in predicting individual tree mortality? by Aitor Vázquez-Veloso, Astor Toraño Caicoya, Felipe Bravo, Peter Biber, Enno Uhl, Hans Pretzsch

“…We use Logistic binomial Regression as the reference algorithm for predicting individual tree mortality. …”
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Use of machine learning to predict creativity among nurses: a multidisciplinary approach by Rola H. Mudallal, Majd T. Mrayyan, Mohammad Kharabsheh

“…This study was aimed to explore the factors influencing nurses’ creativity and to develop a decision support system using machine learning to predict creativity levels among nurses. Methods A multidisciplinary design comprising machine learning algorithms mixed with a descriptive, cross-sectional, correlational design was implemented to enhance data analysis and decision-making. …”
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Crop yield prediction using machine learning: An extensive and systematic literature review by Sarowar Morshed Shawon, Falguny Barua Ema, Asura Khanom Mahi, Fahima Lokman Niha, H.T. Zubair

“…Eventually, this review offers valuable insights into the state-of-the-art algorithms in crop yield prediction and suggests future directions for researchers aiming to address existing difficulties and limitations.…”
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Prediction of rock type from physical and mechanical properties by data mining implementations by Fatih Bayram

“…The paper’s main objective is to present the applicability of data mining algorithms in rock type determination. The physical and mechanical properties of the rocks were evaluated with different data mining algorithms, and the rock types were predicted 95.6% correctly with the model generated with the Support Vector Machine algorithm. …”
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Assessment of binary prediction of fraudulent advertisements in ATS candidate tracking cloud systems by V. V. Ligi-Goryaev, G. A. Mankaeva, T. B. Goldvarg, S. S. Muchkaeva, E. N. Dzhakhnaeva

“…The abstract describes the construction of a binary classification model for predicting the type of job advertisement in cloud-based ATS (Applicant Tracking Systems) as either legitimate or fraudulent. …”
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Application of machine learning for predicting the incubation period of water droplet erosion in metals by Khaled AlHammad, Mamoun Medraj, Moussa Tembely

“…The performance of various ML algorithms is evaluated while investigating the effect of data transformation techniques on prediction accuracy. …”
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Hybrid A*-Guided Model Predictive Path Integral Control for Robust Navigation in Rough Terrains by Joonyeol Yang , Minhyeong Kang , Seulchan Lee, Sanghyun Kim

“…This article proposes the Hybrid A*-guided Model Predictive Path Integral (MPPI) algorithm augmented with traversability estimation to address the challenges of path planning on uneven terrains. …”
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Fidan: a predictive service demand model for assisting nursing home health-care robots by Feng Zhou, Xin Du, WenLi Li, Zhihui Lu, Shih-Chia Huang

“…In order to provide practical help to nursing staff in nursing homes, we innovatively combine the LightGBM algorithm with the machine learning interpretation framework SHAP (Shapley Additive exPlanations) and use comprehensive data analysis methods to propose a service demand prediction model Fidan (Forecast service demand model). …”
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Software Defect Prediction For Quality Evaluation Using Learning Techniques Ensemble Stacking by Muhammad Romadhona Kusuma, Windu Gata, Sigit Kurniawan, Dedi Dwi Saputra, Supriadi Panggabean

“…This research aims to improve the software quality and effectiveness of zakat management by the National Amil Zakat Agency (BAZNAS) through the development of a software defect prediction model (SDPM). We used machine learning techniques and ensemble stacking approach on the "Masjid Tower" dataset containing 228 records and 34 attributes. …”
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Using active learning selection approach for cross-project software defect prediction by Wenbo Mi, Yong Li, Ming Wen, Youren Chen

“…In this paper, we design an active learning selection algorithm for cross-project defect prediction to alleviate the above problems. …”
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An accurate trajectory tracking method for low-speed unmanned vehicles based on model predictive control by Lifen Wang, Sizhong Chen, Hongbin Ren

“…Abstract Trajectory tracking on a low-speed vehicle using the model predictive control (MPC) algorithm usually assumes a simple road terrain. …”
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A Novel Fuzzy Model Predictive Control of a Gas Turbine in the Combined Cycle Unit by Guolian Hou, Linjuan Gong, Xiaoyan Dai, Mengyi Wang, Congzhi Huang

“…Therefore, aiming at higher control performance of the gas turbine in the gas-steam combined cycle process, a novel fuzzy model predictive control (FMPC) strategy based on the fuzzy selection mechanism and simultaneous heat transfer search (SHTS) algorithm is presented in this paper. …”
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Recurrent Neural Network-Based Model Predictive Control for Multiple Unmanned Quadrotor Formation Flight by Boyang Zhang, Xiuxia Sun, Shuguang Liu, Xiongfeng Deng

“…This paper presents a dynamical recurrent neural network- (RNN-) based model predictive control (MPC) structure for the formation flight of multiple unmanned quadrotors. …”
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Assessment of binary prediction of fraudulent advertisements in ATS candidate tracking cloud systems by V. V. Ligi-Goryaev, G. A. Mankaeva, T. B. Goldvarg, S. S. Muchkaeva, V. V. Dzhakhnaev

“…The abstract describes the construction of a binary classification model for predicting the type of job advertisement in cloud-based ATS (Applicant Tracking Systems) as either legitimate or fraudulent. …”
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Research on Path Tracking of Intelligent Hybrid Articulated Tractor Based on Corrected Model Predictive Control by Liyou Xu, Jiaxing Hou, Xianghai Yan, Mengnan Liu, Junjiang Zhang, Yuan Tao

“…Taking the lateral and longitudinal errors as the target and the speed and articulation angular acceleration as the constraints, a tracking control algorithm based on model predictive control is proposed. …”
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Information-Driven Model Predictive Control With Adaptive Partitioning for Energy Optimization in Automated Electric Vehicles by Shahriar Shahram, Yaser P. Fallah

“…This paper presents a methodology to optimize energy consumption in electric vehicles (EVs) using a Model Predictive Control (MPC) framework integrated with detailed power loss models. …”
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Human-Centric IoT-Driven Digital Twins in Predictive Maintenance for Optimizing Industry 5.0 by Özlem Sabuncu, Bülent Bilgehan

“…Predictive maintenance now heavily relies on digital twins and the Internet of Things (IoT), which allow industrial assets to be monitored and decisions made in real time. …”
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