Comparison of Clustering Algorithms: Fuzzy C-Means, K-Means, and DBSCAN for House Classification Based on Specifications and Price by Dhendy Mardiansyah Putra, Ferian Fauzi Abdulloh

“…This study aims to compare the performance of three clustering algorithms, namely Fuzzy C-Means, K-Means, and DBSCAN, in grouping houses based on their specifications and prices. …”
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CO2 Emission-Constrained Short-Term Unit Commitment Problem Using Shuffled Frog Leaping Algorithm by K. Selvakumar, D. Selvabharathi, R. Palanisamy, T. M. Thamizh Thentral

“…The proposed method aims to determine the optimal start-up and shut-down times for generating units to meet fluctuating loads while minimizing operating costs and CO2 emissions. …”
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Utilizing machine learning to predict MRI signal outputs from iron oxide nanoparticles through the PSLG algorithm by Fatemeh Hataminia, Anahita Azinfar

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Cervical Cancer Prediction Based on Imbalanced Data Using Machine Learning Algorithms with a Variety of Sampling Methods by Mădălina Maria Muraru, Zsuzsa Simó, László Barna Iantovics

“…When detecting the minority class, oversampling achieved an average score of 60.80%, while undersampling scored 41.36%. The logistic regression classifier had the greatest impact on balanced techniques, while random forest achieved promising performance, even before applying balancing techniques. …”
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AVOA and ALO Algorithm for Energy-Efficient No-Idle Permutation Flow Shop Scheduling Problem: A Comparison Study by Yolanda Mega Risma, Dana Marsetiya Utama

“…The implementation of such innovative meta-heuristic algorithms holds the potential to significantly contribute to global energy conservation efforts while enhancing the efficiency of industrial operations. …”
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A genetic algorithm approach to green vehicle routing: Optimizing vehicle allocation and route planning for perishable products by Hayati Mukti Asih, Raden Achmad Chairdino Leuveano, Dhimas Arief Dharmawan, Ardiansyah Ardiansyah

“…Utilizing a Genetic Algorithm (GA), the model demonstrates its effectiveness in achieving near-optimal solutions that balance economic, environmental, and quality-focused goals. …”
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Exploiting the Regularized Greedy Forest Algorithm Through Active Learning for Predicting Student Grades: A Case Study by Maria Tsiakmaki, Georgios Kostopoulos, Sotiris Kotsiantis

“…Active learning is a powerful paradigm that utilizes both labeled and unlabeled data, while RGF serves as an effective decision forest learning algorithm acting as the base learner. …”
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Enhancing Security and Efficiency in IoT Assistive Technologies: A Novel Hybrid Systolic Array Multiplier for Cryptographic Algorithms by Atef Ibrahim, Fayez Gebali

“…Therefore, it is essential to prioritize the effective execution of cryptographic algorithms, as they rely on finite field operations such as multiplication, inversion, and division. …”
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Configuration and dimension optimization of active power Filter in distribution networks using a Multi-Strategy improved algorithm by Tang Bo, Liang Haidong, Yue Xiwen, Zhu Ruijin

“…In order to optimize the layout and capacity of APF connected to the grid, this paper proposes a hybrid Improved algorithm for the economic optimization of APF configurations. …”
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Optimization Algorithm of Adaptive Dual-layer Search Path Planning Based on Left-hand Traffic Rules in Mines by HUANG Jiade, LIU Yong, HU Yunqing, MEI Wenqing

“…This paper introduces an optimization algorithm for adaptive dual-layer search path planning based on the left-hand traffic rules in mining areas, aiming to improve the navigation performance of mine trucks within these areas while ensuring the path safety and the real-time planning. …”
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Investigation of a Multi-Strategy Ensemble Social Group Optimization Algorithm for the Optimization of Energy Management in Electric Vehicles by Aala Kalananda Vamsi Krishna Reddy, Komanapalli Venkata Lakshmi Narayana

“…A multi-strategy ensemble social group optimization algorithm (ME-SGO) to improve the exploration for complex and composite landscapes through distance-based strategy adaption and success-based parameter adaption while incorporating linear population reduction is proposed. …”
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Control Strategy of a Rotating Power Flow Controller Based on an Improved Hybrid Particle Swarm Optimization Algorithm by Ziyang Zhang, Jiaoxin Jia, Waseem Aslam, Abubakar Siddique, Fahad R. Albogamy

“…Notably, this paper introduces intelligent optimization algorithms to this field for the first time, employing an improved hybrid particle swarm optimization (HPSO) algorithm to control the active power while keeping the reactive power constant and subsequently adjusting the reactive power while maintaining the active power steady, thereby achieving power regulation. …”
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Nonuniform Doppler extraction-enhanced multichannel extensive cancellation algorithm for passive radar using Iridium satellite signals by Hongwei Fu, Zhang Zhang, Yu Luo, Tingting Fu, Jianglin Li, Xin Jian, Hao Cha

“…In addition, to address the problem of multipath clutter broadening caused by the dual movement of low-orbit satellites and the PR receiver, this paper proposes a nonuniform Doppler extraction-enhanced multichannel extensive cancellation algorithm (NuDE-mECA) to suppress multipath clutter broadening while preserving near-field low-speed target detection capabilities. …”
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Toward a User-Accessible Spectroscopic Sensing Platform for Beverage Recognition Through K-Nearest Neighbors Algorithm by Luca Montaina, Elena Palmieri, Ivano Lucarini, Luca Maiolo, Francesco Maita

“…This demonstrates the potential for embedding accurate, low-power, and cost-efficient sensors into Internet of Things (IoT) devices for real-time nutritional monitoring, reducing the need for user input while enhancing accessibility and usability.…”
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RHS-YOLOv8: A Lightweight Underwater Small Object Detection Algorithm Based on Improved YOLOv8 by Yifan Wei, Jun Tao, Wenjun Wu, Donghua Yuan, Shunzhi Hou

“…Compared with other cutting-edge underwater object detection algorithms, the present algorithm improves the detection accuracy while lightweighting the improvement, which effectively enhances the capability to detect small underwater objects.…”
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Optimizing Radial Distribution Network Performance Through Microgrid Integration Using a Hybrid PSO-HSA Algorithm by Demsew Mitiku Teferra, Livingstone M. H. Ngoo, George N. Nyakoe

“…The performance of the radial distribution system is significantly improved by the microgrid when optimized using the hybrid PSO-HSA algorithm. For the IEEE_15-bus radial distribution system, for example, the VSI improves to 0.932, 0.919, and 0.936, while the AVDI is minimized to 0.00016, 0.00022, and 0.00013 using the PSO, HSA, and hybrid PSO-HSA algorithms, respectively. …”
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Developing a Robust Fuzzy Inference Algorithm in a Dog Disease Pre-Diagnosis System for Casual Owners by Kwang Baek Kim, Doo Heon Song, Hyun Jun Park

“…We evaluated three fuzzy inference algorithms—PFCM-R, FHAL, and MNFL. While PFCM-R achieved high accuracy with clean data, it struggled with noisy inputs. …”
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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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Benchmarking Machine Learning Algorithms for Bearing Fault Classification Using Vibration Data: A Deployment-Oriented Study by Prasanta Kumar Samal, R. Srinidhi, Pramod Kumar Malik, H. J. Manjunatha, Imran M. Jamadar

“…This study presents a comprehensive benchmarking of 33 machine learning (ML) algorithms for bearing fault classification using vibration data, with a focus on real-world deployment in condition monitoring systems. …”
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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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