Towards few-shot learning with triplet metric learning and Kullback-Leibler optimization by Yukun Liu, Xiaojing Wei, Daming Shi, Dan Xiang, Junliu Zhong, Hai Su

“…In training, the deep learning and expectation-maximization algorithm are used to optimize models. Intensive experiments have been conducted on three popular benchmark datasets, and the experimental results show that this method significantly improves the classification ability of few-shot learning tasks and obtains the most advanced performance.…”
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Detection and Optimization of Photovoltaic Arrays’ Tilt Angles Using Remote Sensing Data by Niko Lukač, Sebastijan Seme, Klemen Sredenšek, Gorazd Štumberger, Domen Mongus, Borut Žalik, Marko Bizjak

“…The modules are grouped into arrays, and tilt angles are optimized using a Simulated Annealing (SA) algorithm, which maximizes simulated solar irradiance while accounting for shadowing, direct, and anisotropic diffuse irradiances. …”
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Nanotechnology and LSTM machine learning algorithms in advanced fuel spray dynamics in CI engines with different bowl geometries by Harish Venu, Manzoore Elahi M. Soudagar, Tiong Sieh Kiong, N. M. Razali, Hua-Rong Wei, Armin Rajabi, V. Dhana Raju, T. M. Yunus Khan, Naif Almakayeel, Erdem Cuce, Huseyin Seker

“…Abstract This study explores the integration of nanotechnology and Long Short-Term Memory (LSTM) machine learning algorithms to enhance the understanding and optimization of fuel spray dynamics in compression ignition (CI) engines with varying bowl geometries. …”
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A hybrid PKI and spiking neural network approach for enhancing security and energy efficiency in IoMT-based healthcare 5.0 by Dipalee D․Rane Chaudhari, Manisha S. Bhende, Aadam Quraishi, Azzah AlGhamdi, Ismail Keshta, Mukesh Soni, Brajesh Kumar Singh, Haewon Byeon, Mohammad Shabaz

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Extraction of Optimal Measurements for Drowsy Driving Detection considering Driver Fingerprinting Differences by Yifan Sun, Chaozhong Wu, Hui Zhang, Yijun Zhang, Shaopeng Li, Hongxia Feng

“…Finally, we selected measurements calculated by IDBCPs that can distinguish drowsy driving to constitute individual drivers’ optimal drowsiness-detection measurement set. To verify the advantages of IDBCPs, the measurements calculated by UCPs and IDBCPs were, respectively, used to build driver-specific drowsiness-detection models: DF_U and DF_I based on the Fisher discriminant algorithm. …”
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Grid structure optimization using slow coherency theory and holomorphic embedding method by Fei Tang, Mo Chen, Yuhan Guo, Jinzhou Sun, Xiaoqing Wei, Jiaquan Yang, Xuehao He

“…Simulation results show that the proposed optimization method effectively improves the synchrony clustering performance and voltage stability of the test systems, offering faster optimization speed and better results compared to other classical algorithms.…”
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Collaborative Routing With Multi-Heuristic Algorithm for Enhanced Delivery Efficiency in Truck-Multi Unmanned Aerial Vehicles Systems by Ramdhan Nugraha, Md Masuduzzaman, Soo Young Shin

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Improving Daily Precipitation Estimates by Merging Satellite and Reanalysis Data in Northeast China by Gaohong Yin, Yanling Zhang, Yuxi Cao, Jongmin Park

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A modified TOPSIS algorithm for the assessment of sports quality in higher education using circular pythagorean fuzzy information by Jiapeng Li, Yitong Zhang

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StomachNet: Optimal Deep Learning Features Fusion for Stomach Abnormalities Classification by Muhammad Attique Khan, Muhammad Shahzad Sarfraz, Majed Alhaisoni, Abdulaziz A. Albesher, Shuihua Wang, Imran Ashraf

“…These algorithms are implemented in parallel to obtain optimal feature vectors. …”
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A Linear Regression Prediction-Based Dynamic Multi-Objective Evolutionary Algorithm with Correlations of Pareto Front Points by Junxia Ma, Yongxuan Sang, Yaoli Xu, Bo Wang

“…Specifically, when the DMOP environment changes, this paper first constructs a spatio-temporal correlation model between various key points of the PF based on the linear regression algorithm; then, based on the constructed model, predicts a new location for each key point in the new environment; subsequently, constructs a sub-population by introducing the Gaussian noise into the predicted location to improve the generalization ability; and then, utilizes the idea of NSGA-II-B to construct another sub-population to further improve the population diversity; finally, combining the previous two sub-populations, re-initializing a new population to adapt to the new environment through a random replacement strategy. …”
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Fault diagnosis of ZDJ7 railway point machine based on improved DCNN and SVDD classification by Zengshu Shi, Yiman Du, Xinwen Yao

“…Aiming at the unbalanced features of the railway point machine sample, an improved quantity learning algorithm for hypersphere coordinate mapping based on SVDD is proposed. …”
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Synergizing GIS and genetic algorithms to enhance road management and fund allocation with a comprehensive case study approach by Ahmed Gouda Mohamed, Fahad K. Alqahtani, ElHassan Reda Ismail, Mohamed Nabawy

“…This innovative approach combines a Geographic Information System (GIS)-based road management model with a fund allocation prioritization strategy, enhanced by an optimization engine via a genetic algorithm. …”
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Committee Machine Learning for Electrofacies-Guided Well Placement and Oil Recovery Optimization by Adewale Amosu, Dung Bui, Oluwapelumi Oke, Abdul-Muaizz Koray, Emmanuel Appiah Kubi, Najmudeen Sibaweihi, William Ampomah

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Artificial Bee Colony Algorithm Based on the Division Between Exploration and Exploitation and Its Application in Esophageal Cancer Prediction by WANG Yingcong, YAN Jun, SUN Junwei, WANG Yanfeng

“…Simultaneously, a search equation is formulated for scout bees that incorporates both search experience and diversified optimal solution information. The proposed algorithm is compared to six other ABC algorithms across 80 benchmark functions, with its superiority evaluated in terms of solution quality, non-parametric tests, convergence speed, and time efficiency. …”
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BSDR: A Data-Efficient Deep Learning-Based Hyperspectral Band Selection Algorithm Using Discrete Relaxation by Mohammad Rahman, Shyh Wei Teng, Manzur Murshed, Manoranjan Paul, David Brennan

“…Hyperspectral band selection algorithms are crucial for processing high-dimensional data, which enables dimensionality reduction, improves data analysis, and enhances computational efficiency. …”
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Personalized Human Thermal Sensation Prediction Based on Bayesian-Optimized Random Forest by Hao Yang, Maoyu Ran

“…Finally, the best-performing model was further optimized using Bayesian methods to enhance hyperparameter tuning efficiency and improve the accuracy of personalized human thermal sensation prediction.…”
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Control optimization for permanent magnet synchronous generators in multi-source power systems by LI Lingyun, LIU Weizhi, WANG Yongxiang, LIU Yang

“…A novel approach was proposed that incorporates a Lagrangian function based on the principles of maximum torque and minimum loss to solve for the direct-axis and quadrature-axis currents, leading to the creation of a voltage stability control strategy that integrates vector control with efficiency optimization control. On this basis, a fuzzy fractional-order super-twisting sliding mode control algorithm was introduced to improve the flexibility and performance of the established control strategy. …”
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Research on Motion Transfer Method from Human Arm to Bionic Robot Arm Based on PSO-RF Algorithm by Yuanyuan Zheng, Hanqi Zhang, Gang Zheng, Yuanjian Hong, Zhonghua Wei, Peng Sun

“…To address this shortcoming, this study presents a motion transfer method from the human arm to a bionic robot arm based on the hybrid PSO-RF (Particle Swarm Optimization-Random Forest) algorithm to improve joint space mapping accuracy and dynamic compliance. …”
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A Computational Sketch-Based Approach Towards Optimal Product Design Solutions by Paschalis Charalampous

“…The proposed approach enables the transformation of simple hand-drawn sketches into digital models suitable for complex computational simulations and design optimization. …”
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