Density Logging Curve Reconstruction Method Based on Bayesian-Optimized CNN-LSTM by LI Hongxi, CHEN Mingjiang, ZHANG Xiankun, YANG Bo, ZHAO Bin, LI Xiansheng, WANG Huanhuan

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A multimodal approach for enhanced disease management in cauliflower crops: integration of spectral sensors, machine learning models and targeted spraying technology by Rohit ANAND, Roaf Ahmad PARRAY, Indra MANI, Tapan Kumar KHURA, Harilal KUSHWAHA, Brij Bihari SHARMA, Susheel SARKAR, Samarth GODARA, Shideh MOJERLOU, Hasan MIRZAKHANINAFCHI

“…This research explored a novel multimodal approach for disease management in cauliflower crops. …”
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Inversion Method Based on Temporal Convolutional Networks for Random Ice Load on Conical Offshore Platforms by Wei Li, Ya Guo, Shuzhao Li, Yang Gao, Yan Qu

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Prediction of Earthquake Death Toll Based on Principal Component Analysis, Improved Whale Optimization Algorithm, and Extreme Gradient Boosting by Chenhui Wang, Xiaotao Zhang, Xiaoshan Wang, Guoping Chang

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Credit card default prediction using ML and DL techniques by Fazal Wahab, Imran Khan, Sneha Sabada

“…This research makes use of the UCI ML repository to access the credit card defaulted customer dataset. …”
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Downscaling of ERA5 reanalysis land surface temperature based on attention mechanism and Google Earth Engine by Shiyu Li, Hong Wan, Qun Yu, Xinyuan Wang

“…The downscaling method proposed in this study can effectively improve the accuracy of ERA5-Land LST downscaling, providing new insights for LST downscaling research.…”
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Microseismic Data-Driven Short-Term Rockburst Evaluation in Underground Engineering with Strategic Data Augmentation and Extremely Randomized Forest by Shouye Cheng, Xin Yin, Feng Gao, Yucong Pan

“…To determine the optimal hyperparameters, the whale optimization algorithm is embedded. …”
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Data-Driven Optimization Method for Recurrent Neural Network Algorithm: Greenhouse Internal Temperature Prediction Model by Kwang Cheol Oh, Sunyong Park, Seok Jun Kim, La Hoon Cho, Chung Geon Lee, Dae Hyun Kim

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Multiclass Fault Diagnosis in Power Transformers Using Dissolved Gas Analysis and Grid Search-Optimized Machine Learning by Andrew Adewunmi Adekunle, Issouf Fofana, Patrick Picher, Esperanza Mariela Rodriguez-Celis, Oscar Henry Arroyo-Fernandez, Hugo Simard, Marc-André Lavoie

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Multi-Temporal Remote Sensing Satellite Data Analysis for the 2023 Devastating Flood in Derna, Northern Libya by Roman Shults, Ashraf Farahat, Muhammad Usman, Md Masudur Rahman

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Causes of Multi-Mechanism Abnormal Formation Pressure in Offshore Oil and Gas Wells by Yang Xu, Jin Yang, Zhiqiang Hu, Quanmin Zhao, Lei Li, Qishuai Yin

“…The research findings highlight the predominant role of the undercompaction mechanism, accounting for approximately 70% of the abnormal high-pressure events in the study area. …”
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Forecasting regional carbon prices in china with a hybrid model based on quadratic decomposition and comprehensive feature screening. by Yaoyang Yi

“…Nonetheless, due to the complexity and non-linear nature of the carbon price, its accurate prediction has always been a research difficulty. This work presents a hybrid model incorporating comprehensive feature screening, optimized quadratic decomposition, and the Optuna-Attention-LSTM prediction method, aiming to improve the accuracy and stability of carbon price prediction. …”
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Optimal Markowitz portfolio using returns forecasted with time series and machine learning models by Damian Ślusarczyk, Robert Ślepaczuk

“…The results showed that by using forecasted returns, we can enhance our portfolio selection based on the Markowitz framework, but it is not a universal solution, and we have to control all the parameters and hyperparameters of selected models. This research paper contributes to the field of Financial Engineering by applying ARIMA-GARCH bootstrapping forecasts and XGBoost forecasts in portfolio optimization and testing a wide range of hyperparameters. …”
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Predictors of Static Postural Loading in Primary-School-Aged Children: Comparing Elastic Net and Multiple Regression Methods by Mohammad Ali Mohseni Bandpei, Reza Osqueizadeh, Hamidreza Goudarzi, Nahid Rahmani, Abbas Ebadi

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Hybrid Harris hawks-optimized random forest model for detecting multi-element geochemical anomalies related to mineralization by Hamid Sabbaghi, Nader Fathianpour

“…Performance of the AML algorithms are extremely dependent to values of their hyperparameters. Because, conclusions of their application can significantly be differed tuning hyperparameters. …”
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Robust Cross-Validation of Predictive Models Used in Credit Default Risk by Jose Vicente Alonso, Lorenzo Escot

“…While many methodologies have been developed, cross-validation is perhaps the most widely accepted, often being part of the model development process by optimizing the hyperparameters of predictive algorithms. This experimental research focuses on evaluating existing robust cross-validation variants to address the issues of validating credit default models. …”
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Breast cancer ultrasound image segmentation using improved 3DUnet++ by Saba Hesaraki, Abdul Sajid Mohammed, Mehrshad Eisaei, Ramin Mousa

“…Therefore, computer-aided cancer diagnosis in ABUS volume is highly expected to help the physician for breast cancer screening. In this research, we presented 3D structures based on UNet, ResUNet, and UNet++ for the automatic detection of cancer in ABUS volume to speed up examination while providing high detection sensitivity with low false positives (FPs). …”
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Rapid Detection of Astaxanthin in Antarctic Krill Meal by Computer Vision Combined with Convolutional Neural Network by Quantong ZHANG, Yao ZHENG, Liu YANG, Shuaishuai ZHANG, Quanyou GUO

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Benchmarking Point Cloud Feature Extraction with Smooth Overlap of Atomic Positions (SOAP): A Pixel-Wise Approach for MNIST Handwritten Data by Eiaki V. Morooka, Yuto Omae, Mika Hämäläinen, Hirotaka Takahashi

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Histopathological image based breast cancer diagnosis using deep learning and bio inspired optimization by Venkata Nagaraju Thatha, M. Ganesh Karthik, Venu Gopal Gaddam, D. Pramodh Krishna, S. Venkataramana, Kranthi Kumar Lella, Udayaraju Pamula

“…Abstract Breast cancer diagnosis remains a crucial challenge in medical research, necessitating accurate and automated detection methods. …”
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