APPLICATION OF ARTIFICIAL NEURON NETWORK AND FUZZY INFERENCE IN THE HOUSEPLANT WATERING INTELLIGENT SYSTEM by Roman Korostenskyi, Igor Olenych

“…The proposed approach ensures an optimal soil moisture level of 50–60%, suitable for plant growth and development, while also reducing the average monthly water consumption by 25–27%. …”
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Thoracoabdominal stab wounds: modern surgical tactics by B. N. Kotiv, I. M. Samokhvalov, V. Ju. Markevich, I. I. Dzidzava, O. V. Barinov, V. V. Suvorov, A. V. Goncharov, K. V. Petukhov

“…The objective was to determine the optimal therapeutic and diagnostic algorithm for thoracoabdominal injury.Material and methods. …”
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Research on Fast SOC Balance Control of Modular Battery Energy Storage System by Jianlin Wang, Shenglong Zhou, Jinlu Mao

“…In recent years, SOC balancing methods based on software algorithms have gained popularity. For instance, intelligent control algorithms are being integrated into battery management systems to optimize control strategies for SOC balancing. …”
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Design and Performance Analysis of Fuzzy Logic Controller for Solar Photovoltaic System by Kumuthawathe Ananda-Rao, Steven Taniselass, Afifah Shuhada Rosmi, Aimi Salihah Abdul Nasir, Nor Hanisah Baharudin, Indra Nisja

“…The research addresses these challenges by optimizing battery charging, preventing overcharging, and enhancing overall system efficiency. …”
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Prediction of shut-off head for centrifugal pumps based on grey theory and GA-BP neural network by Dehui Yu, Jinfeng Zhang, Shouqi Yuan, Wensheng Ma, Xiaobang Bai, Yan Chen, Chao Wang

“…This paper presents a predictive model based on extensive experimental data, employing a back propagation (BP) neural network optimized via grey theory and genetic algorithms (GAs). …”
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DeepLabV3+-Based Semantic Annotation Refinement for SLAM in Indoor Environments by Shuangfeng Wei, Hongrui Tang, Changchang Liu, Tong Yang, Xiaohang Zhou, Sisi Zlatanova, Junlin Fan, Liping Tu, Yaqin Mao

“…The proposed method utilizes MobileNetV3 as the backbone network for DeepLabV3+ to maintain segmentation accuracy while reducing computational demands. In this paper, we introduce a parameter-adaptive Density-Based Spatial Clustering of Applications with Noise (DBSCAN) clustering algorithm incorporating K-nearest neighbors and accelerated by KD-tree structures, effectively addressing the limitations of manual parameter tuning and erroneous annotations in conventional methods. …”
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Stochastic Demand-Side Management for Residential Off-Grid PV Systems Considering Battery, Fuel Cell, and PEM Electrolyzer Degradation by Mohamed A. Hendy, Mohamed A. Nayel, Mohamed Abdelrahem

“…The optimization problem was solved using a genetic algorithm (GA), which efficiently explores the solution space to determine the optimal operating schedules and reduce degradation costs. …”
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Research status and progress on key technologies of intelligent orchard by CUI Hongwei, LU Xiaoxuan, YANG Yaqing, LU Xinyi, MA Hao, JI Jiangtao, JIN Xin, LI Xiuzhen, ZHAO Zimeng, ZENG Ningning

“…By analyzing and processing the collected data, these systems can optimize various orchard production processes such as irrigation, fertilization, flower thinning, pesticide application, and harvesting. …”
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An Explainable Fuzzy Framework for Assessing Preeclampsia Classification by Matías Salinas, Daira Velandia, Leondry Mayeta-Revilla, Ayleen Bertini, Marvin Querales, Fabian Pardo, Rodrigo Salas

“…This work introduces SK-MOEFS, an explainable framework based on fuzzy logic and multi-objective evolutionary optimization, designed to classify preeclampsia risk while generating clinically interpretable rules. …”
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Prediction of Biogas Yield from Codigestion of Lignocellulosic Biomass Using Adaptive Neuro-Fuzzy Inference System (ANFIS) Model by Moses Oluwatobi Fajobi, Olumuyiwa Ajani Lasode, Adekunle Akanni Adeleke, Peter Pelumi Ikubanni, Ayokunle Olubusayo Balogun, Prabhu Paramasivam

“…The Gaussian membership function (Gauss-mf) was implemented for the fuzzification of input variables, while the hybrid algorithm was selected for the learning and mapping of the input-output dataset. …”
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Automatic Calculation of Average Power in Electroencephalography Signals for Enhanced Detection of Brain Activity and Behavioral Patterns by Nuphar Avital, Nataniel Shulkin, Dror Malka

“…The present study proposes a novel methodology for the automated calculation of the average power of EEG signals, with a particular focus on the beta frequency band which is known for its pronounced activity during cognitive tasks such as 2D content engagement. An optimization algorithm is employed to determine the most appropriate digital filter type and order for EEG signal processing, thereby enhancing both signal clarity and interpretability. …”
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Video Temporal Grounding with Multi-Model Collaborative Learning by Yun Tian, Xiaobo Guo, Jinsong Wang, Bin Li, Shoujun Zhou

“…Concurrently, the mechanism for generating pseudo-labels is optimized using the CLIP model’s prior knowledge, bolstering both the accuracy and coherence of these labels while efficiently discarding extraneous temporal fragments. …”
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Research on Mine-Personnel Helmet Detection Based on Multi-Strategy-Improved YOLOv11 by Lei Zhang, Zhipeng Sun, Hongjing Tao, Meng Wang, Weixun Yi

“…In the complex environment of fully mechanized mining faces, the current object detection algorithms face significant challenges in achieving optimal accuracy and real-time detection of mine personnel and safety helmets. …”
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A novel adversarial deep TSK fuzzy classifier with its inverse-free fast training by Limin Mao, Hangming Shi, Yongxin Chou, Jinliang Cong, Mingli Lu, Zekang Bian, Suhang Gu

“…This can facilitate the inverse-free fast deep learning algorithm of AD-TSK while maintaining interpretability. …”
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Integrating Learning-Driven Model Behavior and Data Representation for Enhanced Remaining Useful Life Prediction in Rotating Machinery by Tarek Berghout, Eric Bechhoefer, Faycal Djeffal, Wei Hong Lim

“…Both RF and RexNet undergo hyperparameter optimization using Bayesian methods under variability reduction (i.e., standard deviation) of residuals, allowing the algorithms to reach optimal solutions and enabling fair comparisons with state-of-the-art approaches. …”
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Soil Organic Carbon Prediction and Mapping in Morocco Using PRISMA Hyperspectral Imagery and Meta-Learner Model by Yassine Bouslihim, Abdelkrim Bouasria, Budiman Minasny, Fabio Castaldi, Andree Mentho Nenkam, Ali El Battay, Abdelghani Chehbouni

“…This study presents a novel meta-learner framework that combines multiple machine learning algorithms and spectra processing algorithms to optimize SOC prediction using the PRISMA hyperspectral satellite imagery in the Doukkala plain of Morocco. …”
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RIM-Net: A Real-Imaginary-Magnitude Network for NLOS/LOS Identification in UWB Indoor Positioning Systems by Jiacheng Ni, Fang Li, Shuai Cao, Linsong Li

“…Furthermore, the optimization of the TOA algorithm validated the effectiveness of RIM-Net in localization, achieving an average performance improvement of 9.66%. …”
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Learning atomic forces from uncertainty-calibrated adversarial attacks by Henrique Musseli Cezar, Tilmann Bodenstein, Henrik Andersen Sveinsson, Morten Ledum, Simen Reine, Sigbjørn Løland Bore

“…We propose the Calibrated Adversarial Geometry Optimization (CAGO) algorithm to discover adversarial structures with user-assigned errors. …”
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Tent–PSO-Based Unmanned Aerial Vehicle Path Planning for Cooperative Relay Networks in Dynamic User Environments by Shuyue Liu, Wenmao Zhou, Mingwei Qin, Xin Peng

“…The proper planning of UAV paths can improve user coverage while maintaining communication quality. The traditional particle swarm optimization (PSO) algorithm exhibits strong global search capabilities; however, it suffers from challenges such as uneven search coverage owing to the random distribution of the initial particle positions. …”
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Revised Harmonious Fuzzy Technique for Solving Fully Fuzzy Multi-Objective Linear Fractional Programming Problems by Maher A. Nawkhass

“…The harmonious fuzzy technique HFT aims to find a solution that satisfies the uncertain restraints and optimizes the uncertain objectives while taking into account the uncertainty or fuzziness of the problem parameters. …”
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