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An Effective Fault Diagnosis Technique for Wind Energy Conversion Systems Based on an Improved Particle Swarm Optimization
Published 2022“…First, an efficient feature selection algorithm based on particle swarm optimization (PSO) is proposed. …”
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Novel Multi Center and Threshold Ternary Pattern Based Method for Disease Detection Method Using Voice
Published 2020“…Our approach is a simple and efficient voice-based algorithm in which a multi-center and multi threshold based ternary pattern is used (MCMTTP). …”
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Wearable wrist to finger photoplethysmogram translation through restoration using super operational neural networks based 1D-CycleGAN for enhancing cardiovascular monitoring
Published 2024“…<h3>Background and Motivations</h3><p dir="ltr">Physiological signals, such as the Photoplethysmogram (PPG) collected through wearable devices, consistently encounter significant motion artifacts. Current signal processing techniques, and even state-of-the-art machine learning algorithms, frequently struggle to effectively restore the inherent bodily signals amidst the array of randomly generated distortions. …”
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Multi Agent Reinforcement Learning Approach for Autonomous Fleet Management
Published 2019Get full text
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Digital twin in energy industry: Proposed robust digital twin for power plant and other complex capital-intensive large engineering systems
Published 2022“…Data-driven algorithms with capabilities to predict the system’s dynamic behavior still need to be developed. …”
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Adaptive Secure Pipeline for Attacks Detection in Networks with set of Distribution Hosts
Published 2022“…So far none addresses the use of Threat Intelligence (IT) data in Ensemble Learning algorithms to improve the detection process, nor does it work as a function of time, that is, taking into account what happens on the network in a limited time interval. …”
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Artificial Intelligence Driven Smart Farming for Accurate Detection of Potato Diseases: A Systematic Review
Published 2024“…It has been learned that image-processing techniques overwhelm the existing research and have the potential to integrate meteorological data. …”
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A Novel Partitioned Random Forest Method-Based Facial Emotion Recognition
Published 2025“…The proposed method divides multiple regions (different data lengths) into the feature space, allowing the algorithm to learn more complex decision boundaries. …”
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A Cyber-Physical System and Graph-Based Approach for Transportation Management in Smart Cities
Published 2021“…To efficiently process the incoming big data streams, the proposed architecture uses the Apache GraphX tool with several parallel processing nodes, along with Spark and Hadoop that ultimately provide better performance against various state-of-the-art solutions. …”
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Frontiers and trends of supply chain optimization in the age of industry 4.0: an operations research perspective
Published 2024“…It contributes to the literature by identifying the four OR innovations to typify the recent advances in SC optimization: new modeling conditions, new inputs, new decisions, and new algorithms. Furthermore, we recommend four promising research avenues in this interplay: (1) incorporating new decisions relevant to data-enabled SC decisions, (2) developing data-enabled modeling approaches, (3) preprocessing parameters, and (4) developing data-enabled algorithms. …”
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Various Faults Classification of Industrial Application of Induction Motors Using Supervised Machine Learning: A Comprehensive Review
Published 2025“…In current literature, there are a number of papers that address all these faults using different methods, and this paper compiles the information from the written works for ease of access. Machine learning algorithms are a set of data-driven rules that are able to classify specific faults in induction motors, which will be explained further in this review paper. …”
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The Role of Machine Learning in Diagnosing Bipolar Disorder: Scoping Review
Published 2021“…We identified different machine learning models used in the selected studies, including classification models (18, 55%), regression models (5, 16%), model-based clustering methods (2, 6%), natural language processing (1, 3%), clustering algorithms (1, 3%), and deep learning–based models (3, 9%). …”
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Deep and transfer learning for building occupancy detection: A review and comparative analysis
Published 2022“…This work investigates occupancy detection methods to develop an efficient system for processing sensor data while providing accurate occupancy information. …”
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Fast Transient Stability Assessment of Power Systems Using Optimized Temporal Convolutional Networks
Published 2024“…The proposed algorithm unlocks scalability and system adaptability to operational variability by adopting numeric imputation and missing-data-tolerant techniques. …”