Multi-objective optimization of daylighting performance and solar radiation for building geometry using a hybrid evolutionary algorithm by Shaoyang Lou, Xiaojun Luo, Zhonggou Chen, Zhiji Gao, Ruida Wang, Linjin Feng, Guoyi Zhang, Yanfei Zhang, Ye Zhao, Bei Li

“…A multi-objective evolutionary algorithm named Steady-State Island Evolutionary Algorithm (SSIEA) was applied to optimize the building geometry, ultimately yielding the Pareto front optimal solution. …”
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Filter-Based Feature Selection Using Information Theory and Binary Cuckoo Optimisation Algorithm by Ali Muhammad Usman, Umi Kalsom Yusof, Maziani Sabudin

“…Both were used together with binary cuckoo optimization algorithm BCOA (BCOA-MI and BCOA-EI). The target is to improve classification performance (reduce the error rate and computational complexity) on eight datasets with varying degrees of complexity. …”
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Enhancing MPPT optimization with hybrid predictive control and adaptive P&O for better efficiency and power quality in PV systems by Benabdallah Naima, Belabbas Belkacem, Tahri Ahmed, Habib Benbouhenni, Bouddou Riyadh, Heroual Samira, Zaidi Sarra, Z. M. S. Elbarbary, Salman Arafath Mohammed

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Research on intelligent control of coal slime flotation based on the WOA-GRU model by DOU Zhiheng, WANG Ranfeng, QIN Xinkai, CHAI Yuqing, LI Pinyu, LIU Shutong

“…This model leveraged the GRU's capability to effectively handle the time-delay characteristics inherent in the flotation process, while the WOA was used to optimize network parameters, further improving the identification accuracy. …”
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Methods for Improving Point Cloud Authenticity in LiDAR Simulation for Autonomous Driving: A Review by Yanzhao Yang, Jian Wang, Xinyu Guo, Xinyu Yang, Wei Qin

“…It also proposes future directions to bridge the gap between simulated and real-world data, aiming to optimize hybrid training models for improved autonomous driving applications.…”
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Federated Reinforcement Learning in Stock Trading Execution: The FPPO Algorithm for Information Security by Haogang Feng, Yue Wang, Shida Zhong, Tao Yuan, Zhi Quan

“…The FPPO algorithm demonstrates significant improvements in model performance across various stocks, with average returns enhanced by 3% to 15%. …”
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UAV-based multitier feature selection improves nitrogen content estimation in arid-region cotton by Fengxiu Li, Fengxiu Li, Chongqi Zhao, Chongqi Zhao, Yingjie Ma, Yingjie Ma, Ning Lv, Yanzhao Guo, Yanzhao Guo

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An Improved Diagnosis Approach for Short-Circuit Fault Diagnosis in MPC-Based Current Source Inverter System by Jonggrist Jongudomkarn, Pirat Khunkitti, Apirat Siritaratiwat

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Wear fault diagnosis in hydro-turbine via the incorporation of the IWSO algorithm optimized CNN-LSTM neural network by Fang Dao, Yun Zeng, Yidong Zou, Jing Qian

“…Chaotic mapping, bird flock search, and cosine elite variation strategies are introduced to enhance the WSO algorithm's robust performance, and the CNN-LSTM model's hyperparameters are optimized using the IWSO algorithm to improve the diagnostic performance. …”
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Optimized Hybrid Deep Learning Framework for Early Detection of Alzheimer’s Disease Using Adaptive Weight Selection by Karim Gasmi, Abdulrahman Alyami, Omer Hamid, Mohamed O. Altaieb, Osama Rezk Shahin, Lassaad Ben Ammar, Hassen Chouaib, Abdulaziz Shehab

“…Methods: We present an enhanced hybrid deep learning framework that amalgamates the EfficientNetV2B3 with Inception-ResNetV2 models. The models were integrated using an adaptive weight selection process informed by the Cuckoo Search optimization algorithm. …”
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Optimizing Cancer Detection: Swarm Algorithms Combined with Deep Learning in Colon and Lung Cancer using Biomedical Images by HariKrishna Pathipati, Lova Naga Babu Ramisetti, Desidi Narsimha Reddy, Swetha Pesaru, Mashetty Balakrishna, Thota Anitha

“…Eventually, the whale optimization algorithm (WOA) is used to optimally choose the hyperparameters of the CNN‐BiGRU model. …”
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Smart Agricultural Pest Detection Using I-YOLOv10-SC: An Improved Object Detection Framework by Wenxia Yuan, Lingfang Lan, Jiayi Xu, Tingting Sun, Xinghua Wang, Qiaomei Wang, Jingnan Hu, Baijuan Wang

“…Additionally, Shape Weights and Scale Adjustment Factors are introduced to optimize the loss function. The experimental results show that compared with the original YOLOv10, the model generated by the improved algorithm improves the accuracy by 5.88 percentage points, the recall rate by 6.67 percentage points, the balance score by 6.27 percentage points, the mAP value by 4.26 percentage points, the bounding box loss by 18.75%, the classification loss by 27.27%, and the feature point loss by 8%. …”
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Dual-robot formation transport in random environment and narrow restricted area via improved DDPG navigation by Liang Tang, Ronggeng Ma, Bowen Chen, Yisen Niu

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Maximizing Performance of Geopolymer Mortar: Optimizing Basalt and Carbon Fiber Content Composition by Katarzyna Ewa Buczkowska, Petr Louda, Artem Sharko, Oleksandr Sharko, Dmitry Stepanchikov, Ludek Jancik, Piotr Los, Kinga Plawecka, Van Su Le

“…The identified optimal composition demonstrates the potential for improving performance in composition and weight content.…”
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Improving TMJ Diagnosis: A Deep Learning Approach for Detecting Mandibular Condyle Bone Changes by Kader Azlağ Pekince, Adem Pekince, Buse Yaren Kazangirler

“…This approach has the potential to improve the early detection of TMJ-related condylar bone changes, enabling timely referrals and potentially preventing disease progression.…”
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Development of Spectral Clustering Algorithm in Cognitive Diagnosis Model: Approach for Student’s Psychological Growth by Xiao Chang

“…The spectral clustering (SC) algorithm iterative optimization was combined with a similarity matrix and Laplacian matrix to construct an improved spectral clustering cognitive diagnosis model. …”
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Mechanical and Civil Engineering Optimization with a Very Simple Hybrid Grey Wolf—JAYA Metaheuristic Optimizer by Chiara Furio, Luciano Lamberti, Catalin I. Pruncu

“…Metaheuristic algorithms (MAs) now are the standard in engineering optimization. …”
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A Recommendation Algorithm Based on Restricted Boltzmann Machine by WANG Weibing, ZHANG Lichao, XU Qian

“…In the case where the amount of data is too large, the recommended results output by the RBM model will be broader Besides, many collaborative filtering algorithms currently do not handle large data sets better So, we try to use the deep learning technology to strengthen the personalized recommendation model We propose a hybrid recommendation model combining the bound Boltzmann model and the hidden factor model First, we use the RBM algorithm to generate candidate sets, and score the sparse matrix of the candidate set Then we use the LFM model to sort the candidate results and select the optimal solution for recommendation The hybrid model is validated using used large public datasets It can be seen from the verification that compared with the traditional recommendation model, the proposed method can improve the accuracy of the score prediction…”
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Improved Iterative CD-Spline Approach for Building Boundary Regularization Using Airborne LiDAR Data by Renato Cesar dos Santos, Ayman F. Habib, Mauricio Galo

“…To overcome this limitation, we proposed the Improved Iterative Changeable Degree-Spline (IICDS) that consists of testing several CP configurations, resulting in multiple contour models for each building. …”
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Prediction of Electric Vehicle Mileage According to Optimal Energy Consumption Criterion by Oleksii Chkalov, Roman Dropa

“…By representing the road network as a weighted directed graph tailored to the energy consumption model, an algorithm aids in mileage optimization by determining the optimal path for immediate use. …”
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