Performance Evaluation of a Radial Distribution Network Under Emerging Load Prediction Modeling Approach and DG Integration Using a Particle Swarm Optimization Algorithm by Demsew Mitiku Teferra

“…Load forecasting is conducted using the adaptive neuro-fuzzy inference system (ANFIS), with validation carried out through an artificial neural network (ANN). …”
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Sustainable Electric Micromobility Through Integrated Power Electronic Systems and Control Strategies by Mohamed Krichi, Abdullah M. Noman, Mhamed Fannakh, Tarik Raffak, Zeyad A. Haidar

“…Likewise, a comparative analysis of electric motors, such as PMSM, BLDC, SRM, and IM, highlights their unique advantages for micromobility applications. Battery technologies, including Lithium Iron Phosphate, Nickel Manganese Cobalt, Nickel-Cadmium, Sodium-Sulfur, Lithium-Ion and Sodium-Ion, are evaluated with a focus on energy density, efficiency, and environmental impact. …”
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A 3D lightweight network with Roberts edge enhancement model (LR-Net) for brain tumor segmentation by Qingxu Meng, Weijiang Wang, Hang Qi, Hua Dang, Minli Jia, Xiaohua Wang

“…This balance of efficiency and accuracy makes the proposed network well-suited for practical clinical applications.…”
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Soft computing approaches of direct torque control for DFIM Motor's by Zakariae Sakhri, El-Houssine Bekkour, Badre Bossoufi, Nicu Bizon, Mishari Metab Almalki, Thamer A.H. Alghamdi, Mohammed Alenezi

“…These findings provide valuable insights for researchers and engineers seeking to optimize modern DTC system performance according to the specific needs of their applications.…”
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Meta‐Attention Deep Learning for Smart Development of Metasurface Sensors by Yuan Gao, Wei Chen, Fajun Li, Mingyong Zhuang, Yiming Yan, Jun Wang, Xiang Wang, Zhaogang Dong, Wei Ma, Jinfeng Zhu

“…Abstract Optical metasurfaces with pronounced spectral characteristics are promising for sensor applications. Currently, deep learning (DL) offers a rapid manner to design various metasurfaces. …”
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A novel multi-modal rehabilitation monitoring over human motion intention recognition by Saleha Kamal, Saleha Kamal, Mohammed Alshehri, Yahya AlQahtani, Abdulmonem Alshahrani, Nouf Abdullah Almujally, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…This research lays the groundwork for future real-time HMIR systems in smart rehabilitation and medical monitoring applications.…”
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Time Series Classification Using Federated Convolutional Neural Networks and Image-Based Representations by Felipe A. R. Silva, Omid Orang, Fabricio Javier Erazo-Costa, Petronio C. L. Silva, Pedro H. Barros, Ricardo P. M. Ferreira, Frederico Gadelha Guimaraes

“…Time series classification (TSC) has numerous applications across various domains. This research introduces a federated hybrid TSC method that combines image-based time series representation techniques with Convolutional Neural Networks (CNNs) in a decentralized framework. …”
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High-speed train wheel set bearing analysis: Practical approach to maintenance between end of life and useful life extension assessment by Ali Nawaz Sanjrani, Hong Zhong Huang, Sadiq Ali Shah, Fayaz Hussain, Muhammad Punhal, Attaullah Narejo, Bo Zhang

“…The proposed methodology integrates a vision transformer with a fuzzy logic-based Health and Safety Risk Assessment Matrix (HSRAM) to forecast and identify the health status of bearings based on their degradation stages and predict the remaining useful life, extended useful life, and end-of-life of wheelset bearings. …”
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Next-generation cutting-edge hybrid AI frameworks for predicting rheological properties and CO₂ emissions in alkali-activated concrete by Lu Zhang, Kangning Liu, Ali H. AlAteah, Sadiq Alinsaif, Muhammad Sufian, Ayaz Ahmad

“…The rheological properties of alkali-activated concrete (AAC) are critical for its performance in modern construction applications, where stability, pumpability, and resistance to washout are essential. …”
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Analysis of multiple faults in induction motor using machine learning techniques by Puja Pohakar, Ravi Gandhi, Surender Hans, Gulshan Sharma, Pitshou N. Bokoro

“…In order to surpass these limitations, a new approach by using state-of-the-art machine learning algorithms such as Extreme Gradient Boosting (XGBoost) combined with Fuzzy Inference Systems (FIS) presents a new perspective towards improved accuracy and comprehensibility in fault detection. …”
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Trust-based energy-efficient routing protocol for Internet of things–based sensor networks by Muhammad Ilyas, Zahid Ullah, Fakhri Alam Khan, Muhammad Hasanain Chaudary, Muhammad Sheraz Arshed Malik, Zafar Zaheer, Hamood Ur Rehman Durrani

“…Wireless sensor network works as a base-stone for most of the Internet of things applications. There are severe general and specific threats and technical challenges to Internet of things–based sensor networks which must overcome to ensure adaptation and diffusion of it. …”
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A Predictive Model for the Shear Capacity of Ultra-High-Performance Concrete Deep Beams Reinforced with Fibers Using a Hybrid ANN-ANFIS Algorithm by Hossein Mirzaaghabeik, Nuha S. Mashaan, Sanjay Kumar Shukla

“…This indicates that the proposed model can be effectively employed in real-world design applications.…”
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An approach to forecasting damage due to unfavorable circumstances associated with indistinguishability of source data by V. F. Zolotukhin, A. V. Matershev, L. A. Podkolzina

“…The resulting mono-element fuzzy group is presented, which is also a possible event resulting from the intersection of two necessary events.Results. …”
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The Marine Food Chain in Relation to Biodiversity by Andrew R.G. Price

“…Use of expert systems incorporating “fuzzy logic” are providing useful environmental insights in the ASEAN countries and other parts of the world, and have applications in fishery management and biodiversity conservation.…”
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Machine Learning and Deep Learning for Crop Disease Diagnosis: Performance Analysis and Review by Habiba Njeri Ngugi, Andronicus A. Akinyelu, Absalom E. Ezugwu

“…Preprocessing methods like K-means clustering, Fuzzy C-Means, and PCA, along with ensemble approaches, further improved model accuracy. …”
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2dSpAn-Auto: an automated tool for analysis of two-dimensional dendritic spine images by Shauvik Paul, Rahul Pramanick, Nirmal Das, Ewa Baczynska, Zeinab Bedrood, Tapabrata Chakraborti, Subhadip Basu, Jakub Wlodarczyk

“…., 2dSpAn-Auto.b, that implements binary skeletonization alogrithm and 2dSpAn-Auto.f, that generates fuzzy skeletons directly from gray-scale images. …”
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Evaluation of LSTM, GRU, and ANFIS Models for Ankle Angle and Ankle Moment Prediction Using Biomechanical Data by T. S. Sangeetha, S. N. Muralikrishna, Advay Mandar Naik, Arun P. Parameswaran

“…This study compares the performance of Long Short-Term Memory (LSTM) networks, Gated Recurrent Units (GRU), and Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for predicting ankle angle and ankle moment at walking speeds of 1 km/h, 2 km/h, and 3 km/h. …”
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Research on non-destructive testing method for radial defect of anchor bolt based on longitudinal guided wave by Deying TANG, Weimin TANG, Zhiyi ZENG, Qing TIAN, Ailing LI, Yaling GUO, Erdi A’BI, Tongyu WU, Yibo WU

“…The stripes of the time-frequency graph based on short-time Fourier transform are fuzzy, the resolution is low, and the identification of defect information is not clear. …”
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Global Ionospheric TEC Map Prediction Based on Multichannel ED-PredRNN by Haijun Liu, Yan Ma, Huijun Le, Liangchao Li, Rui Zhou, Jian Xiao, Weifeng Shan, Zhongxiu Wu, Yalan Li

“…These models may result in fuzzy prediction results due to neglecting spatial memory, as spatial memory is crucial for capturing the correlations of TEC within the TEC neighborhood. …”
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Geospatial Data and Deep Learning Expose ESG Risks to Critical Raw Materials Supply: The Case of Lithium by Christopher J. M. Lawley, Marcus Haynes, Bijal Chudasama, Kathryn Goodenough, Toni Eerola, Artem Golev, Steven E. Zhang, Junhyeok Park, Eleonore Lèbre

“…We suggest that this type of geospatial ESG rating is broadly applicable to other CRM and that mapping spatially situated risks prior to mineral exploration has the potential to improve ESG outcomes and government policies that strengthen supply chains.…”
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