The Hubble Image Similarity Project by Richard L. White, J. E. G. Peek

“…These data can be used to assess the accuracy of image-search algorithms based on computer vision methods. …”
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Dealing With Class Imbalance in Uplift Modeling-Efficient Data Preprocessing via Oversampling and Matching by Carla Vairetti, Maria Jose Marfan, Sebastian Maldonado

“…To ensure scalability and effectiveness, we adopt a distributed framework based on MapReduce and utilize a hybrid spill trees algorithm for efficient nearest neighbor search. Our experimental results demonstrate the advantages of the proposed method, achieving statistically superior predictive performance compared to other resampling approaches while maintaining efficiency in terms of overall running times.…”
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SASDL and RBATQ: Sparse Autoencoder With Swarm Based Deep Learning and Reinforcement Based Q-Learning for EEG Classification by Sunil Kumar Prabhakar, Seong-Whan Lee

“…<italic>Methods</italic>: The main advantage of using deep learning when compared to other machine learning algorithms is that it has the capability to accomplish feature engineering on its own. …”
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Surface Quality Monitoring and Improvement for Dimensional Metrology in Inline CT by Denoising with Neural Networks and Fast Surface Quality Metric by Faizan Ahmad, Ahmed Baraka, César Cardona-Marin, Steffen Kieß, Dominik Wolfschläger, Robert H. Schmitt, Sven Simon

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Motion multi-object matching and position estimation based on unsynchronized image sequences by Kai Guo, Rui Cao, Chenyang Yue, Faxin Li, Xin Zhou, Binbin Wang

“…Finally, synthetic data and real images are used to experimentally test the performance of our proposed method, and it is compared with the matching algorithm under synchronized images based on epipolar constraint. …”
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Improving energy efficiency for intelligent reflecting surface assisted PD-NOMA in EH relaying network by Hong Nguyen-Thi, Thuc Kieu-Xuan, Thang Le-Nhat, Anh Le-Thi

“…To determine the efficiency of PSO, we consider two other techniques: Genetic Algorithm (GA) and Exhaustive Search (ES). Finally, we evaluate the proposed model's performance in different scenarios, such as the number of IRS elements and the number of relay nodes, the relaying selection strategies, and the transmit power at the BS. …”
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Optimal Computation Offloading Decisions Based on System Utility and Cost Balance by Bingxue Zhang, Xisheng Li, Jia You

“…Based on the new evaluation model, an objective function is constructed to minimize the system&#x2019;s cost-utility ratio, and an improved particle swarm optimization algorithm with enhanced search capabilities is proposed to solve it by designing a computation offloading strategy. …”
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THE EFFICIENCY ANALYSIS OF MULTI-AGENT OPTIMIZATION METHODS OF AIRCRAFT DESIGNS ELEMENTS by A. V. Panteleev, M. S. Karane

“…The research describes strategies for finding solutions to multi-agent metaheuristic algorithms, such as: fish school search, krill herd, and imperialist competition algorithm. …”
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Surgical Treatment of Neuroendocrine Liver Metastases by Ser Yee Lee, Peng Chung Cheow, Jin Yao Teo, London L. P. J. Ooi

“…There is no firm consensus on the optimal treatment strategy for NELM. A systematic search of the PubMed database was performed from 1995–2010, to collate the current evidence and formulate a sound management algorithm. …”
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Real-time and Cost-efficient Indoor Localization and Mapping Solution for Emergency Response Applications by H. Elsayed, A. Shaker

“…The resulting maps are continuously being optimized using a loop-closing algorithm to reduce drift and maintain the trajectory integrity. …”
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Genetic detection of Theileria annulata from Bos taurus and Bubalus bubalis during health surveillance at marsh breeders' farm in Basra Marshes, Iraq. by Noor Hammed, Majid Bannai, Muna Jori

“…The results were then compared to international isolates via an analysis of genetic nucleotide sequences using the Basic Local Alignment Search Tool (BLASTn) algorithm, available at the National Center for Biotechnology Information (NCBI). …”
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An incremental learning framework for pipeline weld crack damage identification and leakage rate prediction by Jing Huang, Zhifen Zhang, Yanlong Yu, Yongjie Li, Shuai Zhang, Rui Qin, Ji Xing, Wei Cheng, Guangrui Wen, Xuefeng Chen

“…Secondly, the depth first search algorithm is combined with the radial basis function neural network to perform online increment labelling of the leakage state. …”
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Rapid Lactic Acid Content Detection in Secondary Fermentation of Maize Silage Using Colorimetric Sensor Array Combined with Hyperspectral Imaging by Xiaoyu Xue, Haiqing Tian, Kai Zhao, Yang Yu, Ziqing Xiao, Chunxiang Zhuo, Jianying Sun

“…Moreover, two optimization algorithms, namely grid search (GS) and crested porcupine optimizer (CPO), were compared to determine their effectiveness in optimizing the parameters of the SVR model. …”
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A secure and energy-efficient routing using coupled ensemble selection approach and optimal type-2 fuzzy logic in WSN by S. Ambareesh, Pundalik Chavan, S. Supreeth, Rajesh Nandalike, P. Dayananda, S. Rohith

“…To deal with those challenges, we advocate a novel routing framework that is both steady and power-efficient, leveraging an Improved Type-2 Fuzzy Logic System (IT2FLS) optimized by means of the Reptile Search Algorithm (RSA). This modern framework employs weighted ensemble clustering and matched ensemble choice techniques, facilitating strong cluster formation and resulting in a substantial 98% development in community lifetime, an 80% enhancement in packet delivery ratio (PDR), and a 45% reduction in average power consumption while as compared to current protocols. …”
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Electric Vehicle Charging Load Forecasting Method Based on Improved Long Short-Term Memory Model with Particle Swarm Optimization by Xiaomeng Yang, Lidong Zhang, Xiangyun Han

“…By combining the global search capability of the PSO algorithm with the advantages of LSTM networks in time-series modeling, a PSO-LSTM hybrid framework optimized for seasonal variations is developed. …”
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Scheduling and Evaluation of a Power-Concentrated EMU on a Conventional Intercity Railway Based on the Minimum Connection Time by Yinan Wang, Limin Xu, Xiao Yang, Jingjing Bao, Feng Lin, Yiwei Guo, Yixiang Yue

“…In the second stage, an improved ant colony algorithm is designed to arrange and combine the internal running lines in each plan to improve the search quality and convergence speed, which changes the pheromone volatilization coefficient with iteration. …”
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Optimal Canceling of the Physiological Tremor for Rehabilitation in Parkinson’s Disease by Behnam Faraji, Zahra Esfahani, Kourosh Rouhollahi, Davood Khezri

“…Furthermore, to enhance the feasibility of the suggested control strategy, the coefficients of the controller were determined using a hybrid version of the harmony search and cuckoo optimization algorithm. Results: The advantages of the applied method include decreasing hand tremors and applied electric field intensity to the brain; consequently, it leads to reducing adverse effects, such as muscle contraction and speech disorders. …”
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Model Selection from Multiple Model Families in Species Distribution Modeling Using Minimum Message Length by Zihao Wen, David L. Dowe

“…To find the relevant features efficiently, we further develop a novel search algorithm that does not require calculating the message length for all possible subsets of features. …”
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PSA-Optimized Compressor Speed Control Strategy of Electric Vehicle Thermal Management Systems by Kun Xia, Lianglu Yu, Jingxia Wang, Wei Yu

“…This study proposes a control strategy based on the PID Search Algorithm (PSA), ensuring optimal thermal management for an integrated battery and cabin TMS. …”
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A machine learning approach to population pharmacokinetic modelling automation by Sam Richardson, Itziar Irurzun Arana, Andrzej Nowojewski, Diansong Zhou, Jacob Leander, Weifeng Tang, Richard Dearden, Megan Gibbs

“…This approach was evaluated on one synthetic and four clinical datasets, with results compared to manually developed models. Results Here we show that the automated approach reliably identifies model structures comparable to manually developed expert models in less than 48 h on average (40-CPU, 40 GB environment) while evaluating fewer than 2.6% of the models in the search space. …”
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