Enhancing water saturation predictions from conventional well logs in a carbonate gas reservoir with a hybrid CNN-LSTM model by Ali Gohari Nezhad, Mohammad Emami Niri

“…The methodology includes data pre-processing to de-noise and transform data into a proper format, feature engineering followed by feature selection based on domain knowledge, models’ training, testing, and optimizing. XGBoost hyperparameters were tuned using grid search, and each neural network model was optimized using a genetic algorithm. …”
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AI-powered blockchain technology in industry 4.0, a review by Mohsen Soori, Roza Dastres, Behrooz Arezoo

“…Blockchain ensures the integrity and immutability of IoT data, while AI can analyze this data for insights and optimization. …”
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Research on Fast SOC Balance Control of Modular Battery Energy Storage System by Jianlin Wang, Shenglong Zhou, Jinlu Mao

“…In recent years, SOC balancing methods based on software algorithms have gained popularity. For instance, intelligent control algorithms are being integrated into battery management systems to optimize control strategies for SOC balancing. …”
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Vehicle Relocation Triggering Thresholds Determination in Electric Carsharing System under Stochastic Demand by Wanjing Ma, Lei Wang, Lin Li

“…The solution algorithm employed the min–max robust optimization to tackle the uncertainty and the Pareto optimum to decide the solution under dual objectives. …”
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Does the COVID-19 pandemic affect the asset allocation performance? Evidence from a composite asset selection approach by Jung-Bin Su

“…The proposed approaches in this study can be embedded in a computer as an asset allocation algorithm of Robo-advisers.…”
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Development of a standardized data collection and intelligent fabric quality prediction system for the weaving department by Ning Dai, Lunjun Li, Kaixin Xu, Zhehao Lu, Xudong Hu, Yanhong Yuan

“…This study leverages the standardization and interoperability features of open platform communications unified architecture technology to facilitate data acquisition within the weaving department, establishing a reliable Internet of Things framework that supports subsequent fabric quality prediction, and optimizing the back propagation neural network through the K-means clustering algorithm and particle swarm optimization to predict the type and number of fabric defects. …”
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Application research of 3D virtual interactive technology in interactive teaching of arts and crafts by Mingqi Yao

“…For this reason, the research proposes an image denoising model based on convolutional neural network and wavelet transform, which adopts residual neural network structure and batch normalization algorithm, aiming at gradient explosion and gradient disappearance that may be caused by convolutional neural network, And the problem of low training efficiency has been optimized. …”
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An Inter-Regional Lateral Transshipment Model to Massive Relief Supplies with Deprivation Costs by Shuanglin Li, Na Zhang, Jin Qin

“…Specifically, JADE is employed in the first stage to allocate the volume of massive relief supplies, aiming to minimize deprivation costs, while IALNS optimizes intermodal routing in the second stage to minimize the weighted sum of transportation time and cost. …”
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Research on image generation technology based on deep learning by Li Jinchen

“…Based on the above problems, this paper analyzes the methods of improving and optimizing the mainstream image generation algorithm from the perspectives of improving and optimizing the loss function, improving the space modeling, revising the structure of both the generator and discriminator, while speeding up the training process. …”
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External archive guided radial-grid multi objective differential evolution by Vikas Palakonda, Samira Ghorbanpour, Jae-Mo Kang, Heechul Jung

“…Abstract Differential evolution (DE) is a robust evolutionary algorithm for solving single-objective and multi-objective optimization problems (MOPs). …”
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A comparative study of ultra-massive MIMO intelligent receivers with adversarial robustness and energy efficiency for 6G applications by Pushkar Nidagundi, Advesh Darvekar, Malik Amber, Ramesh R

“…The Taguchi method yields up to 40 % improvement in energy efficiency while maintaining near-perfect BER. Practical implications of massive power consumption, system complexity, and execution time are discussed, alongside a comparative analysis with recent neural network and genetic algorithm optimizations. …”
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DeepLabV3+-Based Semantic Annotation Refinement for SLAM in Indoor Environments by Shuangfeng Wei, Hongrui Tang, Changchang Liu, Tong Yang, Xiaohang Zhou, Sisi Zlatanova, Junlin Fan, Liping Tu, Yaqin Mao

“…The proposed method utilizes MobileNetV3 as the backbone network for DeepLabV3+ to maintain segmentation accuracy while reducing computational demands. In this paper, we introduce a parameter-adaptive Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm incorporating K-nearest neighbors and accelerated by KD-tree structures, effectively addressing the limitations of manual parameter tuning and erroneous annotations in conventional methods. …”
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Machine learning-driven design of wide-angle impedance matching structures for wide-angle scanning arrays by Sina Hasibi Taheri, Javad Mohammadpour, Ali Lalbakhsh, Slawomir Koziel, Stanislaw Szczepanski

“…Optimal WAIM parameters are efficiently determined using a genetic algorithm (GA). …”
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Soil Organic Carbon Prediction and Mapping in Morocco Using PRISMA Hyperspectral Imagery and Meta-Learner Model by Yassine Bouslihim, Abdelkrim Bouasria, Budiman Minasny, Fabio Castaldi, Andree Mentho Nenkam, Ali El Battay, Abdelghani Chehbouni

“…This study presents a novel meta-learner framework that combines multiple machine learning algorithms and spectra processing algorithms to optimize SOC prediction using the PRISMA hyperspectral satellite imagery in the Doukkala plain of Morocco. …”
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A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques by Suganya Athisayamani, Tamilazhagan S, A. Robert Singh, Jae-Yong Hwang, Gyanendra Prasad Joshi

“…XGBoost optimizes decision tree ensembles and provides class probabilities, while the ANN processes numerical data to learn deeper representations. …”
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APPLICATION OF ARTIFICIAL NEURON NETWORK AND FUZZY INFERENCE IN THE HOUSEPLANT WATERING INTELLIGENT SYSTEM by Roman Korostenskyi, Igor Olenych

“…The proposed approach ensures an optimal soil moisture level of 50–60%, suitable for plant growth and development, while also reducing the average monthly water consumption by 25–27%. …”
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Flexible Configurable Modular Neural Network-Based OFDM Receiver by A. B. Sergienko, P. V. Apalina, A. D. Lebedinskaya

“…The proposed OFDM receiver for all considered modulation types provided error rates comparable to those of the baseline algorithms under favorable channel conditions (moderate delay spread with low Doppler spread) and outperformed baseline algorithms in severe conditions (channel with a large delay spread and high Doppler spread). …”
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Visualized hysteroscopic artificial intelligence fertility assessment system for endometrial injury: an image-deep-learning study by Bohan Li, Hui Chen, Hua Duan

“…The incidence of AS in patients with infertility and recurrent miscarriage can be as high as 10%, while the pregnancy rate in cases of moderate to severe adhesions can be as low as 34%. …”
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Research status and progress on key technologies of intelligent orchard by CUI Hongwei, LU Xiaoxuan, YANG Yaqing, LU Xinyi, MA Hao, JI Jiangtao, JIN Xin, LI Xiuzhen, ZHAO Zimeng, ZENG Ningning

“…Using LiDAR, vision-based navigation, and obstacle avoidance algorithms, machinery can complete tasks safely and efficiently. …”
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Thoracoabdominal stab wounds: modern surgical tactics by B. N. Kotiv, I. M. Samokhvalov, V. Ju. Markevich, I. I. Dzidzava, O. V. Barinov, V. V. Suvorov, A. V. Goncharov, K. V. Petukhov

“…The objective was to determine the optimal therapeutic and diagnostic algorithm for thoracoabdominal injury.Material and methods. …”
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