DenseNet-FPA: Integrating DenseNet and Flower Pollination Algorithm for Breast Cancer Histopathology Image Classification by Musa Adamu Wakili, Harisu Abdullahi Shehu, Mahdi Abdollahi, Badamasi Imam Ya'u, Md Haidar Sharif, Huseyin Kusetogullari

“…DenseNet effectively extracts hierarchical features, while FPA optimizes the selection of the most discriminative features, improving classification accuracy and reducing computational overhead. …”
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Expansion of Output Spatial Extent in the Wavenumber Domain Algorithms for Near-Field 3-D MIMO Radar Imaging by Yifan Gong, Limin Zhai, Yan Jia, Yongqing Liu, Xiangkun Zhang

“…To suppress aliasing while expanding the output spatial extent, an optimization approach for the wavenumber domain algorithms is proposed. …”
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The Lightweight Fracture Segmentation Algorithm for Logging Images Based on Fully 3D Attention Mechanism and Deformable Convolution by Qishun Yang, Liyan Zhang, Zihan Xi, Yu Qian, Ang Li

“…Experimental results demonstrate that SWSDS-Net achieves optimal performance across all evaluation metrics in this task, delivering superior visual results in fracture segmentation while successfully overcoming limitations present in existing algorithms such as complex shapes, noise interference, and low-quality images. …”
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EsoDetect: computational validation and algorithm development of a novel diagnostic and prognostic tool for dysplasia in Barrett’s esophagus by Migla Miskinyte, Benilde Pondeca, José B. Pereira-Leal, Joana Cardoso

“…In evaluating the value of gene expression for diagnosis and prognosis, the analyzed datasets allowed for the ranking of biomarkers, resulting in eighteen diagnostic genes and fifteen prognostic genes that were used for further algorithm development. Ultimately, a linear support vector machine algorithm incorporating ten genes was identified for diagnostic application, while a radial basis function support vector machine algorithm, also utilizing ten genes, was selected for prognostic prediction. …”
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Long and short term fault prediction using the VToMe-BiGRU algorithm for electric drive systems by Lihui Zheng, Xu Fan, Zongshan Kang, Xinjun Jin, Wenchao Zheng, Xiaofen Fang

“…Specifically, the VToMe algorithm achieves stable detection of medium to long term system faults, while the BiGRU network achieves rapid fault prediction in the short term. …”
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RSM-YOLOv11: Lightweight Steel Surface Defect Segmentation Algorithm Research Based on YOLOv11 Improvement by Zenghai Shan, Hu Haoyan, Changjian Zhu, Shaowen Du, Hongtao Jing, Wang Haibin

“…The model size is reduced by 23.81%, and the computational cost is decreased by 15.38%. While maintaining a lightweight structure, it outperforms existing mainstream algorithm models. …”
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A node deployment algorithm for maximizing network lifetime in delay-constrained duty-cycled wireless sensor networks by Thi-Nga Dao, Seokhoon Yoon

“…Then, a non-deterministic algorithm is proposed to derive the optimal number of nodes in each circular layer that meets given constraints and maximizes network lifetime. …”
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Determining Point of Economic Cattle Milk Production through Machine Learning and Evolutionary Algorithm for Enhancing Food Security by Sonam Bhardwaj, Ayon Tarafdar, Manoj Baghel, Triveni Dutt, Gyanendra Kumar Gaur

“…Artificial neural networks (ANNs) in conjugation with genetic algorithms (GAs) have been demonstrated to be an effective tool for system modelling and optimization in a variety of applications. …”
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Multiobjective Cognitive Cooperative Jamming Decision-Making Method Based on Tabu Search-Artificial Bee Colony Algorithm by Fang Ye, Fei Che, Lipeng Gao

“…Most of the existing studies about jamming decision only pay attention to the jamming benefits, while ignoring the jamming cost. In addition, the conventional artificial bee colony algorithm takes too many iterations, and the improved ant colony (IAC) algorithm is easy to fall into the local optimal solution. …”
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A Monte Carlo Tree Search-Based Load Balancing Algorithm for 6G Indoor Heterogeneous Networks by Guanghui Ma, Syifaul Fuada, Marcos Katz

“…By dynamically predicting future network states, the proposed algorithm optimally distributes traffic, improving overall network performance. …”
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Influence of Genetic Algorithm Parameters on Their Performance for Parameter Identification of a Yeast Fed-batch Fermentation Process Model by Maria Angelova, Tania Pencheva

“…Almost all applied SGA and MGA led to similar values of the optimization criterion but the SGA with operators’ sequence mutation, crossover and selection, and MGA with operators’ sequence crossover, selection and mutation, are significantly faster than others while keeping the model accuracy. …”
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Improvement analysis of organic light emitting diode temperature control by integrating whale algorithm in PID control system. by Dayu Zhang, Cong Guan

“…To solve this problem, the study proposes an improved PID controller based on the Long Short-Term Memory (LSTM) optimized by the Whale Optimization Algorithm (WOA). …”
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Research on Adaptive Planning of Three-Dimensional Trajectory for Uncrewed Aerial Vehicle Inspection Based on Nonlinear Weibull Algorithm by Zhuang Liu, Ning Yang, Jiaxing Fu, Huanqing Cai, Xuebei Wei

“…An S-shaped characteristic function-based nonlinear evolution factor is employed to balance global exploration and local exploitation of the optimal path, while a Weibull flight operator mutation strategy is designed to enable the algorithm to escape from locally optimal paths, enrich the search space, and improve convergence accuracy. …”
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Mixed Integer Nonlinear Programming-Based Unit Commitment of Conventional Thermal Generators Using Hybrid Evolutionary Algorithms by Syed Arslan Ali Shah, Noor Hussain Mugheri, Riaz Hussain Memon, Aamir Ali Bhatti, Muhammad Usman Keerio

“…Therefore, in this paper, hybrid EA based on a Genetic Algorithm (GA) has been applied to find the optimal solution to the UC problem. …”
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Enhanced Community Detection via Convolutional Neural Network: A Modified Approach Based on MRFasGCN Algorithm by Puneet Kumar, Dalwinder Singh, Mamoona Humayun, Ali Alqazzaz, Arun Malik, Ibrahim Alrashdi, Isha Batra, Ghadah Naif Alwakid

“…After Experiments NMI value for MRFasGCN on DBLP data set is 0.662 while for Modified MRFasGCN it is 0.672, Modified MRFasGCN algorithm provides significant improvement of 2.9% in performance as compared to MRFasGCN. …”
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A Study of Multi-distributed Resource Equalization Allocation for Virtual Power Plants Based on Genetic-heuristic Algorithm by Haifeng Li, Tao Jin, Xian Xu, Lin Shi

“…Combining the global search capability of a genetic algorithm and the local optimization capability of an ant colony algorithm, the genetic algorithm stage adopts real-number encoding and a dynamic crossover-mutation strategy, while the ant colony algorithm stage optimizes the pheromone update mechanism to avoid premature convergence. …”
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Comparison of K-Nearest Neighbors and Naive Bayes Classifier Algorithms in Sentiment Analysis of 2024 Election in Twitter (X) by Lola Enjelia, Yana Cahyana, Rahmat, Deden Wahiddin

“…This study compares the performance of the K-Nearest Neighbors (K-NN) and Naive Bayes Classifier (NBC) algorithms in sentiment analysis of the 2024 Regional Election (Pilkada) based on Indonesian local data sourced from platform X. …”
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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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K-Nearest Neighbor and Naive Bayes Classifier Algorithm in Determining The Classification of Healthy Card Indonesia Giving to The Poor by Yofi Firdan Safri, Riza Arifudin, Much Aziz Muslim

“…This can be seen from the accuracy of determining the feasibility of K-Nearest Neighbor algorithm of 64%, while the combination of K-Nearest Neighbor-Naive Bayes Classifier algorithm is 96%, so the combination of K-Nearest Neighbor-Naive Bayes Classifier algorithm is the optimal algorithm in determining the feasibility of healthy Indonesian card recipients with an increase of 32% accuracy. …”
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Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques by Rabiu Aminu, Samantha M. Cook, David Ljungberg, Oliver Hensel, Abozar Nasirahmadi

“…The concept of explainable artificial intelligence was adopted by incorporating permutation feature importance ranking and Shapley Additive explanations values to identify the feature set that optimized a model's performance while reducing computational complexity. …”
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