An EfficientNet integrated ResNet deep network and explainable AI for breast lesion classification from ultrasound images by Kiran Jabeen, Muhammad Attique Khan, Ameer Hamza, Hussain Mobarak Albarakati, Shrooq Alsenan, Usman Tariq, Isaac Ofori

“…After that, a new feature selection technique is proposed based on the cuckoo search algorithm called cuckoo search controlled standard error mean. …”
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Tomato Leaf Disease Identification Framework FCMNet Based on Multimodal Fusion by Siming Deng, Jiale Zhu, Yang Hu, Mingfang He, Yonglin Xia

“…Furthermore, to enhance both training efficiency and parameter optimization capabilities of the model, we introduce a Multi-strategy Improved Coati Optimization Algorithm (MSCOA). This algorithm integrates Good Point Set initialization with a Golden Sine search strategy, thereby boosting global exploration, accelerating convergence, and effectively preventing entrapment in local optima. …”
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Migration and mutation (MeTa) hybrid trained ANN for dynamic spectrum access in wireless body area network by Geoffrey Eappen, Shankar T, Rajesh A

“…The novel MeTa hybrid optimization algorithm achieves a balance between global and local search abilities by optimizing the weights of the ANN. …”
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Study on Energy Saving and Optimization Controlof Metro Vehicle Based on Coasting Control by HUANG Jian, QUJianwei

“…According to characteristics of metro vehicle operation and energy consumption characteristics, combined with optimized trainhandling method, an energy optimization algorithm of quick search for coasting point was presented. …”
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A FAULT DIAGNOSIS METHOD BASED ON IMPROVED ARTIFICAL BEE COLONY OPTIMIZE SUPPORT VECTOR MACHINE by WU YinHua, XU QiongYan

“…Aiming at the fact that the fault diagnosis performance of support vector machine（ SVM） highly depends on the parameters selection,a fault diagnosis method based on improved artificial bee colony（ IABC） optimize SVM was proposed. In order to improve search ability of ABC,Levy flight strategy was introduced and improved the original ABC algorithm. …”
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Radiation protection measures during endourological therapies by Lazaros Tzelves, Patrick Juliebø-Jones, Ioannis Manolitsis, Themistoklis Bellos, Ioannis Mykoniatis, Marinos Berdempes, Titos Markopoulos, Michael Lardas, Belthangady M. Zeeshan Hameed, Panagiotis Angelopoulos, Amelia Pietropaolo, Bhaskar Somani, Ioannis Varkarakis, Andreas Skolarikos

“…Objective: The objective of this narrative review was to search the existing literature for studies reporting measures to minimize radiation use during endoscopic management of stone disease and present ways of reducing the exposure of both patients and operating room staff. …”
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An XGBoost-SHAP Model for Energy Demand Prediction With Boruta–Lasso Feature Selection by Yiwen Wang, Weibin Cheng, Yuting Jin, Jifei Li, Yantian Yang, Shaobing Hu

“…This study proposes an interpretable ML framework for energy demand prediction based on the Boruta-Lasso two-stage feature selection model, extreme gradient boosting (XGBoost) regression model, grid search optimization algorithm, and Shapley additive explanations (SHAP) algorithm. …”
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Analisis Perbandingan Algoritma Djikstra, A-Star, dan Floyd Warshall dalam Pencarian Rute Terdekat pada Objek Wisata Kabupaten Dompu by Rusydi Umar, Anton Yudhana, Andi Prayudi

“…In this study using real objects that display the actual location using the Leaflet.js platform and different parameters, from this study will compare the performance of the Dijkstra, A * and Floyd Warshall Algorithms for the process of finding other tourist information using the PHP programming language. …”
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Multi-Time-Scale Layered Energy Management Strategy for Integrated Production, Storage, and Supply Hydrogen Refueling Stations Based on Flexible Hydrogen Load Characteristics of Po... by Zhuoyu Jiang, Rujie Liu, Weiwei Guan, Lei Xiong, Changli Shi, Jingyuan Yin

“…Compared with traditional optimization algorithms, it can effectively improve the ability to search for the optimal solution. …”
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Deep neural network based distribution system state estimation using hyperparameter optimization by Gergő Békési, Lilla Barancsuk, Bálint Hartmann

“…The study uses data from four real-life low-voltage supply areas in Hungary, which were modeled to address the challenges in obtaining network information. Compared to traditional methods like the weighted least squares method, the Tree-structured Parzen Estimator algorithm significantly improves the accuracy of the voltage amplitude and angle estimations, reducing the relative error by 14–73%. …”
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Reliability assessment of elastic distribution network based on fault correlation matrix by LI Ning, HU Jiale, ZHAN Xiaoxuan, SHEN Panpan, JIANG Panyong, ZHUO Chaoran

“…The final results show that the calculation time of the proposed method is only about 0.055s, which is reduced by 87% and 75% respectively compared with that of the fault diffusion algorithm and the block algorithm.…”
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Improving Earth surface temperature forecasting through the optimization of deep learning hyper-parameters using Barnacles Mating Optimizer by Zuriani Mustaffa, Mohd Herwan Sulaiman, Muhammad ‘Arif Mohamad

“…The forecasting model is trained on a global temperature dataset with seven inputs and compared with DL models optimized by Particle Swarm Optimization (PSO), Harmony Search Algorithm (HSA), and Ant Colony Optimization (ACO). …”
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Simultaneous Wood Defect and Species Detection with 3D Laser Scanning Scheme by Zhao Peng, Li Yue, Ning Xiao

“…Second, a deep preferred search algorithm is used to segment the retained defect points marked with different colors. …”
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LightGBM-Based Human Action Recognition Using Sensors by Yinuo Liu, Ziwei Chen

“…Through simulation experiments, it is demonstrated that the feature extraction method proposed in this paper has improved the accuracy of HAR. Compared with classical machine learning algorithms such as random forest (version 1.5.2) and XGBoost (version 2.1.3), the LightGBM algorithm shows improved performance in terms of the accuracy rate, which reaches 94.98%. …”
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Integrating Multi-Layer Perceptron Regression with Innovative Optimization for Accurate Building Cooling Load Prediction by Subhiya Zeynalli, Baharak Eslami

“…Through a hybridization technique with two cutting-edge optimization algorithms, the Brown Bear Optimization Algorithm (BBOA) and the Non-Monopolize Search Algorithm (NMSA), it sets out to explore its optimization potential. …”
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Intelligent optimization method for hazardous materials transportation routing with multi-mode and multi-criterion collaborative constraints by Fan Chen, Qing Zhu

“…Subsequently, leveraging non-dominated sorting and crowding distance algorithms to assess the merit of multi-objective solutions, a local search strategy is introduced. …”
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Fault Diagnosis and Data Reconstruction of Temperature Sensors for Wind Turbine Stator Winding by Ling Zhou, Qiancheng Zhao, Jinhui Zeng, Anfeng Zhu, Xiafei Long, Ling He

“…The method combines supervisory control and data acquisition (SCADA) with an improved firefly sparrow search algorithm (FISSA)–optimized deep belief network (DBN). …”
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Cooperative Spectrum Sensing for Cognitive Heterogeneous Networking Using Iterative Gauss-Seidel Process by Haleh Hosseini, Kaamran Raahemifar, Sharifah Kamilah Syed Yusof, Alagan Anpalagan

“…This method with low complexity can minimize the cost using the golden section search method in a finite number of iterations. ROC curves are depicted using the achieved probability of detection and false alarm by numerical examples to illustrate the efficiency of the proposed algorithm. …”
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Improved Water Level Retrieval in Complex Riverine Environments: Sentinel‐3 and Sentinel‐6 Altimetry Over China's Rivers by Chenqi Fang, Di Long, Qi Huang, Fanyu Zhao, Huaichuan Liu, Xingwu Duan, Aizhong Hou

“…This study presents an Improved Multiple Subwaveform Analysis (IMSA) algorithm based on the 50% Threshold and Ice‐1 Combined (TIC) algorithm, incorporating noise filtering into the subwave search module and refining the retracking strategy for multiple subwaves, independent of coarse digital elevation models (DEMs). …”
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Identification of the intestinal type gastric adenocarcinoma transcriptomic markers using bioinformatic and gene expression analysis by V. V. Volkomorov, E. S. Grigor’eva, G. S. Krasnov, N. V. Litvyakov, N. A. Lisitsyn, M. I. Voevoda, A. V. Belkovets, S. G. Afanas’ev, N. V. Cherdyntseva

“…Then, the expression levels of the mRNAs in 55 pare clinical specimens were investigated using reverse transcription polymerase chain reaction.Results. Comparative analysis of the mRNA levels in normal and tumor tissues using a new bioinformatics algorithm allowed to identify 3 high-copy transcripts (SULF1, PMEPA1 and SPARC), intracellular content of which markedly increased in GC. …”
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