A mixed modeling approach to predict the effect of environmental modification on species distributions. by Francesco Cozzoli, Menno Eelkema, Tjeerd J Bouma, Tom Ysebaert, Vincent Escaravage, Peter M J Herman

“…Sustainable development requires the ability to predict responses of species to anthropogenic pressures. …”
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EVALUATION OF THE MODEL PREDICTION TOXICITY (LD50) FOR SERIES OF 42 ORGANOPHOSPHORUS PESTICIDES by HANANE FIKRI, TAOUFIQ FECHTALI, MOHAMED MAMOUMI

“… Structure-Toxicity Relationships have been studied for a set of 42 organophosphorous pesticides (OPs) through multiple linear regression (MLR) and artificial neural networks (ANN). A model with three descriptors, including: total lipophilicity [log (P)], widths radicals R1 [(LR1)] and R2 [(LR2)] has achieved good results in phase Training and phase prediction of toxicity [log LD50 (lethal dose 50, Oral rat)]. …”
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An interpretable machine learning model for precise prediction of biomarkers for intermittent fasting pattern by Xiaoli Hu, Qingjun Xu, Xuan Ma, Lin Li, Yongning Wu, Feifei Sun

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A risk prediction model for gastric cancer based on endoscopic atrophy classification by Yadi Lan, Weijia Sun, Shen Zhong, Qianqian Xu, Yining Xue, Zhaoyu Liu, Lei Shi, Bing Han, Tianyu Zhai, Mingyue Liu, Yujing Sun, Hongwei Xu

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Load Prediction Based on Hybrid Model of VMD-mRMR-BPNN-LSSVM by Gang Zhang, Hongchi Liu, Pingli Li, Meng Li, Qiang He, Hailiang Chao, Jiangbin Zhang, Jinwang Hou

“…Finally, each component is input into the prediction model together with its feature set, in which back propagation neural network (BPNN) is used to predict high-frequency components, least square-support vector machine (LS-SVM) is used to predict intermediate and low frequency components, and BPNN is also used to integrate the prediction results to obtain the final load prediction value, and compare the prediction results of method in this paper with that of the prediction models such as autoregressive moving average model (ARMA), LS-SVM, BPNN, empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), and VMD. …”
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Optimizing malicious website prediction: An advanced XGBoost-based machine learning model by Hussain Sumaira, Zada Islam, Alazab Moutaz, Alfraihi Hessa, Aldhayan Manal, Ullah Inam, Khan Mohammad Asmat Ullah

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Modelling on Car-Sharing Serial Prediction Based on Machine Learning and Deep Learning by Nihad Brahimi, Huaping Zhang, Lin Dai, Jianzi Zhang

“…After comparing the obtained results using different metrics, we found that CNN-LSTM outperformed other methods to predict the future car usage. Meanwhile, the model using all the different feature categories results in the most precise prediction than any of the models using one feature category at a time…”
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Heartbeat information prediction based on transformer model using millimetre‐wave radar by Bojun Hu, Biao Jin, Hao Xue, Zhenkai Zhang, Zhaoyang Xu, Xiaohua Zhu

“…This study proposes a heartbeat prediction method based on the transformer model using millimetre‐wave radar. …”
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A deep learning model for predicting systemic lupus erythematosus-associated epitopes by Jiale He, Zixia Liu, Xiaopo Tang

“…These findings underscore the model’s robustness and capacity to generalize across complex epitope prediction tasks. …”
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Using Gradient Boosting Regression to Improve Ambient Solar Wind Model Predictions by R. L. Bailey, M. A. Reiss, C. N. Arge, C. Möstl, C. J. Henney, M. J. Owens, U. V. Amerstorfer, T. Amerstorfer, A. J. Weiss, J. Hinterreiter

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Prediction of China’s Silicon Wafer Price: A GA-PSO-BP Model by Jining Wang, Hui Chen, Lei Wang

“…The BP (Back-Propagation) neural network model (hereafter referred to as the BP model) often gets stuck in local optima when predicting China’s silicon wafer price, which hurts the accuracy of the forecasts. …”
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Modeling and Prediction of Conducted Interference ofElectric Vehicle Motor Drive System by LIU Songlin, YANG Tianfan, ZHI Yongjian, MIN Jianjun

“…At present, EMI suppression for this port is usually based on empirical trial and error method in the industry, which lacks a set of accurate system level EMI simulation prediction models for quantitative EMC risk assessment. …”
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Voice as a sensitive biomarker for predicting exercise intensity: a modelling study by Shuyi Zhou, Ruisi Ma, Wangjing Hu, Dandan Zhang, Rui Hu, Shengwei Zou, Dingyi Cai, Zikang Jiang, Hexiao Ding, Ting Liu

“…These features were analyzed using statistical models, including support vector machine (SVM), to classify exercise intensity.ResultsSignificant variations in speech characteristics, such as speech duration, fundamental frequency (F0), and pause times, were observed across different exercise intensities, with the models achieving high accuracy in distinguishing between exercise states.ConclusionThese findings suggest that speech analysis can provide a non-invasive, real-time method for monitoring exercise intensity. …”
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Complex Model for Hot Metal Temperature Prediction: Torpedo Car and Ladle Processes by Milan Durdán, Ján Terpák, Marek Laciak, Ján Kačur, Patrik Flegner, Gabriel Tréfa

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Explicit and Implicit Feature Contrastive Learning Model for Knowledge Graph Link Prediction by Xu Yuan, Weihe Wang, Buyun Gao, Liang Zhao, Ruixin Ma, Feng Ding

“…The results validate that our model outperforms the state-of-the-art baselines in link prediction tasks.…”
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Multistep Prediction Model for Photovoltaic Power Generation Based on Time Convolution and DLinear by WANG Shuyu, LI Hao, MA Gang, YUAN Yubo, BU Qiangsheng, YE Zhigang

“…[Methods] This paper presents a multistep prediction model for photovoltaic power generation based on a temporal convolutional network （TCN） and DLinear combined model. …”
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A Modified Fatigue Damage Model for High-Cycle Fatigue Life Prediction by Meng Wang, Qingguo Fei, Peiwei Zhang

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A Fractal Prediction Model for the Friction Coefficient of Wet Clutch Friction Plates by Jianfeng Cao, Sirui Yang, Zhigang Chen, Haoxuan Sun, Fenglian Ning, Heyun Bao

“…A comparative experiment between the joint motion state and dynamic simulation is performed, concluding that the micro convex contact model has certain accuracy in predicting the contact state of friction plates under various working conditions.…”
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Predicting Remaining Useful Life Based on Hilbert–Huang Entropy with Degradation Model by Yuhuang Zheng

“…To assess the degradation of a machine, this paper presents a bearing remaining useful life (RUL) prediction method. The method relies on a novel health indicator and a linear degradation model to predict bearing RUL. …”
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The application of the motivation-opportunity-ability model in predicting green entrepreneurial behavior of farmers by Zobeyde Kouchaky, Fatemeh Razzaghi Borkhani, Taher Azizi-Khalkheili, Fatemeh Ghorbani Piralidehi

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