Optimization of Geometric Characteristics of Cycloidal Profiles of Gerotor Hydraulic Machines by S. O. Kireev, A. R. Lebedev, M. V. Korchagina

“…The basic research method was modeling the gerotor machine profile using Mathcad computer mathematics system. …”
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Breast Cancer Classification with Various Optimized Deep Learning Methods by Mustafa Güler, Gamze Sart, Ömer Algorabi, Ayse Nur Adıguzel Tuylu, Yusuf Sait Türkan

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Predicting Days on Market to Optimize Real Estate Sales Strategy by Mauro Castelli, Maria Dobreva, Roberto Henriques, Leonardo Vanneschi

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Reflection Reduction on DDR3 High-Speed Bus by Improved PSO by Huiyong Li, Hongxu Jiang, Bo Li, Miyi Duan

“…Additionally, an improved particle swarm optimization algorithm with adaptive perturbation is presented to solve the impedance mismatch problem (IPSO-IMp) based on the above model. …”
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Fractional Optimizers for LSTM Networks in Financial Time Series Forecasting by Mustapha Ez-zaiym, Yassine Senhaji, Meriem Rachid, Karim El Moutaouakil, Vasile Palade

“…These results suggest that fractional-order optimization holds significant promise for improving financial forecasting models—provided that the fractional parameters are carefully tuned to balance memory effects with system stability.…”
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TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5 by Han Wang, Zhenwei Yang, Qiaoshou Liu, Qiang Zhang, Honggang Wang

“…Finally, the EIOU loss function is introduced to measure the overlap between the predicted box and the real box more accurately and improve the detection accuracy. The test results of KITTI and CCTSDB2021 public traffic datasets show that compared with the original YOLOv5 model, the improved algorithm reduces the number of parameters by 20%, the calculation amount by 21%, and mAP@0.5 by 1.0%. …”
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RESEARCH ON PERFORMANCE PREDICTION OF THIN SEAM SHEARER BY COMBINING GENETIC ALGORITHM WITH BP NEURAL NETWORK by ZHAO LiJuan, JIN ZhongFeng

“…Established mathematical model of thin seam shearer,we use genetic algorithm to optimize the weighted values and threshold values of the BP neural network,using the simulation data for training and testing samples,and then use the BP algorithm to train the neural network,thus avoiding the local minimum values when the training is done with the BP neural network alone. …”
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Quality of Experience Optimization for AR Service in an MEC Federation System by Huong Mai do, Tuan Phong Tran, Myungsik Yoo

“…To address this shortcoming, we studied AR subtask offloading and resource allocation in a multi-hop, multi-access edge computing federation. Our approach improves the quality of experience (QoE) by optimizing video quality and reducing delay while ensuring fairness, which is modeled as the ratio between provided and required quality. …”
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FONDUE—Fine-Tuned Optimization: Nurturing Data Usability & Efficiency by Valerie Restat, Indra Diestelkämper, Meike Klettke, Uta Störl

“…As an adaptive and easily extendable framework, FONDUE operates similarly to proven methods of database query optimization. Analogously, it consists of the following parts: Rule-based optimization, where the appropriate data cleaning algorithms are selected based on use case constraints, optimizer hints in the form of best practices, and cost-based optimization, where the costs are measured in terms of data quality. …”
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A dual-phase deep learning framework for advanced phishing detection using the novel OptSHQCNN approach by Srikanth Meda, Vangipuram Sesha Srinivas, Killi Chandra Bhushana Rao, Repudi Ramesh, Narasimha Rao Yamarthi

“…The final phase involves classifying the data using the Shallow hybrid quantum-classical convolutional neural network (SHQCNN) model. To improve the effectiveness of the classification approach, the hyperparameters present in the SHQCNN model are fine-tuned using the shuffled shepherd optimization algorithm (SSOA). …”
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Efficiency Optimization of PMSM-Type Elevator Machine: An Industrial Comparison by Mucahit Soyaslan, Osman Eldogan, Ahmet Fenercioglu, Yusuf Avsar, Nurdogan Ceylan, Muhammed Salih Sarıkaya

“…Critical parameters, including stator tooth tip thickness, slot tip radius, slot height, stator yoke height, stator tooth thickness, and the number of turns per phase, were optimized to enhance efficiency. The artificial bee colony (ABC) algorithm was utilized for the first time to determine the optimal configuration of an external rotor PMSM. …”
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Analysis of the thermal distribution of a porous radial fin influenced by an inclined magnetic field with neural computing by Shazia Habib, Waseem, Zeeshan Khan, Salah Boulaaras, Mati ur Rahman, Saeed Islam, Rafik Guefaifia

“…This innovative approach offers a sophisticated solution for complex thermal models, improved prediction accuracy for nonlinear heat transfer, parameter-driven optimization in porous media heat transfer, and increased model efficiency for real-time thermal management.…”
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Heating Load Prediction with Meta-Heuristic ‎Algorithms and Adaptive Neuro-Fuzzy ‎Inference System Integration by Seyed Hadi Seyed Hatami, Reza Seifi Majdar

“…To enhance predic-tive accuracy, two meta-heuristic algorithms, the Reptile Search Algorithm (RSA) and the Flow Direction Algorithm (FDA), are seamlessly integrated into the Adaptive Neuro-Fuzzy Inference System (ANFIS) model. …”
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The Evolution of Portfolio Theory: Integrating Machine Learning with Markowitz Optimization by Xu Junhao

“…An empirical analysis utilizing recent U.S. market data reveals that ML models improve risk assessment, asset selection, and adaptive portfolio allocation. …”
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Critical Component Overheating Monitoring Algorithm Integrating Temperature-sensing Patches and Computer Vision Trains by SHU Dong, ZHANG Beijia, YANG Hongtai

“…In the test on a real dataset, the improved algorithm achieves an accuracy rate of 99.30%.…”
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A Fast and Efficient Beamforming Algorithm Imitating Plant Growth Gene for Phased Array Antenna by Jinling Zhang, Chen Han, Zhanqi Zheng, Xiongzhi Zhu, Xiaohui Li

“…This algorithm converts the complex optimization process of array antenna excitation by the classical optimization algorithm into a simple process of fine-tuning the gain at any angle on the beam to make it grow and approach the target pattern. …”
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IMPROVE OF UNCERTAIN MICROSATELLITE MAGNETIC CLEANLINESS BASED ON MAGNETIC FIELD SPATIAL HARMONICS COMPENSATION by Б.І. Кузнецов, Т.Б. Нікітіна, І.В. Бовдуй, К.В. Чуніхін, В.В. Коломієць, Б.Б. Кобилянський

“…Both vector game solution calculated based on particles multi-swarm optimization (PMSO) algorithms from Pareto optimal solutions taking into account binary preference relations. …”
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Enhanced NDVI prediction accuracy in complex geographic regions by integrating machine learning and climate data—a case study of Southwest basin by Zehui Zhou, Jiaxin Jin, Bin Yong, Weidong Huang, Lei Yu, Peiqi Yang, Dianchen Sun

“…To address these limitations, this study developed an NDVI time-series prediction optimization model, LSKRX, which integrates multiple machine learning algorithms with local geographic and climatic data. …”
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A cooperative stochastic configuration network based on differential evolutionary sparrow search algorithm for prediction by Wenhao Fang, Bo Shen, Anqi Pan, Lei Zou, Baoye Song

“…To improve the prediction accuracy of the network, a cooperative stochastic configuration network (CSCN) based on a novel differential evolutionary sparrow search algorithm (DESSA), termed as DESSA-CSCN, is proposed. …”
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Vertical Handover Decision Algorithm Using Ants’ Colonies for 4G Heterogeneous Wireless Networks by Imad El Fachtali, Rachid Saadane, Mohammed ElKoutbi

“…The concept is based on QoS aware ant colony built on the vertical handoff mechanism that uses an updated version of ants’ colony optimization decision algorithm (ACOR), the dynamic and static factors such as RSS, the cost of service, bandwidth, the velocity of MT, the power consumption and security, and the module for predicting the traveling distance within an IEEE 802.11 WLAN cell. …”
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