Optimization of Graphene Oxide’s Characteristics with TOPSIS Using an Automated Decision-Making Process by Javanbakht T.

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Exploring explainable machine learning algorithms to model predictors of tobacco use among men in Sub Sahara Africa between 2018 and 2023 by Mequannent Sharew Melaku, Nebebe Demis Baykemagn, Lamrot Yohannes, Adem Tsegaw Zegeye

“…STATA version 17 was used for data cleaning and descriptive statistics, while Python 3.9 was employed for machine learning predictions. The study utilized several machine learning models, including Decision Tree, Logistic Regression, Random Forest, KNN, eXtreme Gradient Boosting (XGBoost), and AdaBoost, to identify the key predictors of tobacco use among men. …”
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Enhancing patient rehabilitation outcomes: artificial intelligence-driven predictive modeling for home discharge in neurological and orthopedic conditions by Leonardo Buscarini, Paola Romano, Elena Sofia Cocco, Carlo Damiani, Sanaz Pournajaf, Marco Franceschini, Francesco Infarinato

“…Progress in both fields has enabled the generation of a vast amount of data used for making predictions and identifying interesting clusters and pathways. …”
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Explainable Model Prediction of Memristor by Sruthi Pallathuvalappil, Rahul Kottappuzhackal, Alex James

“…This article proposes predicting the memristor device under test by automatically evaluating the <italic>I&#x2013;V</italic> behavior using random forest and extreme gradient boosting algorithms. …”
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The machine learning in the prediction of elections by M.S.C. José A. León-Borges, M.A. Roger-Ismael-Noh-Balam, Lic. Lino Rangel Gómez, Br. Michael Philip Strand

“…This research article, presents an analysis and a comparison of three different algorithms: A.- Grouping method K-means, B.-Expectation a convergence criteria, EM and C.- Methodology for classification LAMDA, using two software of classification Weka and SALSA, as an aid for the prediction of future elections in the state of Quintana Roo. …”
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Research on POI quality prediction based on KPCA-GA-BP neural network by Lu LIU, Dan YANG, Ruijie CHEN, Jia LI, Xi ZHOU

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Evaluation of Thermal Damage Effect of Forest Fire Based on Multispectral Camera Combined with Dual Annealing Algorithm by Pan Pei, Xiaojian Hao, Ziqi Wu, Rui Jia, Shenxiang Feng, Tong Wei, Wenxiang You, Chenyang Xu, Xining Wang, Yuqian Dong

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Mopidip: a modular real-time pipeline for machinery diagnosis and prognosis based on deep learning algorithms by Mattia Pujatti, Davide Calzà, Andrea Gobbi, Piergiorgio Svaizer, Marco Cristoforetti

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Prediction of Scale Synchronization Instability by V. E. Lankin, A. K. Schaschkin

“…Based on the models of long-term care scales algorithms to estimate parameters of these processes and their prediction are created. …”
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LSTM-ANN-GA A HYBRID DEEP LEARNING MODEL FOR PREDICTIVE MAINTENANCE OF INDUSTRIAL EQUIPEMENT by Farouk Noumich, Abouchabaka Jaafar, Amrani Ayoub

Subjects: “…predictive maintenance…”
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Operational Performance Assessment of PV-Powered Street Lighting: A Comparative Study of Different Machine Learning Prediction Models by Safwan Nadweh, Nabil Mohammed, Charalambos Konstantinou, Shehab Ahmed

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A novel wind speed prediction model based on neural networks, wavelet transformation, mutual information, and coot optimization algorithm by Faezeh Amirteimoury, Farshid Keynia, Elaheh Amirteimoury, Gholamreza Memarzadeh, Hanieh Shabanian

“…To tackle this issue, this paper proposes a new wind speed prediction model that combines four techniques: Discrete Wavelet Transform, which smooths the wind speed signal; Mutual Information, which selects the most informative part of the wind speed time series; Coot Optimization Algorithm for optimal feature selection; and Bidirectional Long Short-Term Memory for capturing complex patterns. …”
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Enhanced Prediction of California Bearing Ratio (CBR) Values in Geotechnical Engineering Using Decision Tree Algorithm and Meta-Heuristic Optimizations by Linda Davies, Dominik Jánošík

“…This paper presents a novel approach to the accurate prediction of CBR values. Using the DT algorithm, the method creates complex and incredibly accurate predictive models. …”
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Modeling and Predicting the Changes in Hearing Loss of Workers with the Use of a Neural Network Data Mining Algorithm: A Field Study by Sajad ZARE, Mohammad Reza GHOTBIRAVANDI, Hossein ELAHISHIRVAN, Mostafa Ghazizadeh AHSAEED, Mina ROSTAMI, Reza ESMAEILI

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Advanced reference crop evapotranspiration prediction: a novel framework combining neural nets, bee optimization algorithm, and mode decomposition by Ahmed Elbeltagi, Okan Mert Katipoğlu, Veysi Kartal, Ali Danandeh Mehr, Sabri Berhail, Elsayed Ahmed Elsadek

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Bus Arrival Time Prediction Based on the Optimized Long Short-Term Memory Neural Network Model With the Improved Whale Algorithm by Bing Zhang, Lingfeng Tang, Dandan Zhou, Kexin Liu, Yunqiang Xue

“…This article proposes using the improved whale optimization algorithm–long short-term memory (IWOA–LSTM) model to predict bus arrival times and improving the whale algorithm by optimizing the hyperparameters of the LSTM model, so that the advantages and disadvantages of the whale algorithm and the LSTM model can complement each other, thus enhancing the robustness of the model. …”
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An online clustering algorithm predicting model for prostate cancer based on PHI-related variables and PI-RADS in different PSA populations by Jiyuan Hu, Qi Miao, Jiayi Ren, Hongbo Su, Xianlu Zhang, Jianbin Bi, Gejun Zhang

“…Some researches have created nomograms for predicting risk, but these are not easily visualized. …”
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DGCA3QM: DESIGN OF A DUAL GENETIC ALGORITHM BASED AUTOREGRESSION MODEL FOR CORRELATIVE PREDICTION OF AIR QUALITY METRICS by Harna M. Bodele, G. M. Asutkar, Kiran G. Asutkar

“…To overcome these issues, this text proposes design of a Dual Genetic Algorithm (DGA) based Auto regression model for Correlative prediction (AC) of Air Quality Metrics. …”
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Spatial-temporal evolution characteristics and driving factors of carbon emission prediction in China-research on ARIMA-BP neural network algorithm by Sanglin Zhao, Zhetong Li, Hao Deng, Xing You, Jiaang Tong, Bingkun Yuan, Zihao Zeng

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A diagnostic prediction model for anti-neutrophil cytoplasmic antibody associated vasculitis combined with glomerulonephritis based on machine learning algorithm by Wang Jian-mei, Zhu Ge-li, Cao Chen-lin, Peng Qing-quan

“…The model had significant predictive power， with an area under the curve （AUC） of 1.000. …”
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