Fault prediction model in wind turbines using deep learning structure with enhanced optimisation algorithm Mahendra Bhatu Gawali, Swapnali Sunil Gawali, Megharani Patil Journal of Control and Decision, 2025 Digital Twin (DT) is used for lifetime monitoring of the drive train and can be a costly option. This proposal adopts the predictive modelling of wind turbines by digital twins by deep learning strategies. Initially, the data is acquired from publicly available wind turbine datasets. Next, the deep features and statistical features are extracted, and the autoencoder is adapted to get the deep features. Then, the Enhanced Marine Predators Algorithm (EMPA) is to select the optimal weighted fused features, where the EMPA would tune the weights used for fusion and the features selection. Finally, the predictive modelling is done via a newly recommended Adaptive Deep Temporal Convolution Network with an Attention Mechanism (ADTCN-AM). It is tuned for precise outcomes with the help of EMPA for forecasting the wind speed and predicting the generated power. The comparative performance analysis of the recently used wind prediction system model shows better efficient results.
A Systematic Survey on Machine Learning Classifier Systems to Address Class Imbalance Nitin L. Shelake, Mahendra Gawali 2024 3rd International Conference on Artificial Intelligence Computational Electronics and Communication System Aicecs 2024, 2024 Class imbalance is a significant obstacle in machine learning, causing biased model results and constraining generalization abilities. This systematic survey reviews machine learning classifier systems designed to mitigate class imbalance challenges. The objective is to analyze the effectiveness of various techniques in overcoming imbalance hurdles. The survey defines class imbalance and its implications for model training and evaluation. It categorizes approaches into data-level, algorithm-level, and hybrid methods, including oversampling, undersampling, cost-sensitive learning, ensembles, and deep learning. Each category is explored to provide insights into strengths, limitations, and applicability. Evaluation metrics tailored for imbalanced datasets are scrutinized, emphasizing the importance of metrics prioritizing minority class performance. Challenges in evaluating classifier systems in imbalanced settings are discussed, with guidance on metric selection. Recent advancements and trends in handling class imbalance, such as active learning and interpretable methods, are highlighted. Key challenges like scalability, interpretability, and algorithmic robustness are identified, with discussions on open research directions. This survey aims to offer a comprehensive understanding of classifier systems for class imbalance, aiding researchers and practitioners. By synthesizing recent literature and analyzing imbalance challenges, this study contributes to advancing knowledge in this vital area of machine learning
Advancing Offshore Wind Turbine Energy Generation Prediction Through Comparative Analysis and Novel Machine Learning Techniques Chaitanya P. Kale, Mahendra B. Gawali 2024 IEEE International Conference on Smart Power Control and Renewable Energy Icspcre 2024, 2024 The necessity for this work arises from the critical need to accurately predict energy generation from offshore wind turbines, pivotal in ensuring efficient energy management and grid integration process. While existing studies have made strides, they are often limited by their reliance on simplistic models or a lack of comprehensive comparative analyses. To address these limitations, this paper proposes a novel approach integrating advanced machine learning (ML) algorithms with state-of-the-art techniques. The proposed model leverages a comprehensive comparative analysis of ML algorithms, including Linear Regression, Random Forest, Gradient Boosting, Support Vector Machines (SVM), and Neural Networks (NN), to identify the most effective predictive model. By considering parameters such as tower height and blade length, the model achieves superior accuracy and robustness in energy generation prediction. Furthermore, this study introduces novel methodologies, including ensemble learning, transfer learning, explainable AI (XAI), ML techniques to enhance predictive performance and interpretability sets. By incorporating advanced time-series analysis and Bayesian optimization, the model captures temporal dependencies and efficiently optimizes hyperparameters, respectively, elevating its predictive capabilities. The impact of this work extends beyond academia, with implications for industry stakeholders involved in offshore wind energy production. Accurate energy generation predictions empower decision-makers to optimize turbine design and placement, ultimately advancing the transition towards sustainable energy solutions. Moreover, the integration of XAI techniques fosters trust and usability in real-world applications, bridging the gap between predictive accuracy and interpretability sets.
A novel human-to-robot interaction model based on transfer expert reinforcement learning with recurrent neural network Mahendra Bhatu Gawali, Swapnali Sunil Gawali, Megharani Patil, Anand Khandare Journal of Autonomous Intelligence, 2024 <p>The control tasks related to interaction tracking are mainly limited in robot manipulators-based traditional applications. In this, the desired motivations are specified based on the trajectories and the desired positions. The robots are programmed by using the teach-and-playback method in such applications that are assumed to be more convenient. Moreover, the advancements in sensing and robotic methodologies fulfill the satisfactory requirements of more demanding tasks. Several instructions are provided for interacting robots with humans in order to perform a sequence of more difficult tasks. It does not require learning the motions, but it only requires learning the positions of the motions in such applications, and this position is learned by using the robot controller. The major aim of this research work is to develop a new Transfer Expert Reinforcement Learning (TERL) method to offer efficient interaction between humans and computers. In this developed model, Reinforcement Learning (RL) is utilized to observe the movement of the robotic arm. Then, robot movement is considered with the help of a deep learning approach named Recurrent Neural Network (RNN) along with inputs of kinematic movement. Finally, the proposed model achieves a superior rate than conventional approaches in human to human-to-robot interaction model.</p>
Intelligent Model for Smart Waste Detection and Segmentation using YOLO v8 Saurabh Hon, Shekhar Bhide, Dipjyot Jape, Kishor More, Tejas Nagare, M. B. Gawali International Conference on Intelligent and Innovative Practices in Engineering and Management 2024 Iipem 2024, 2024 Object detection is a crucial domain with applications across multiple disciplines. It has demonstrated a significant impact on predicting objects in videos and images. Presently, the majority of cities face the challenge of garbage disposal, making it difficult for humans to segregate waste by category. To tackle this enduring challenge, we propose implementing smart waste detection and segmentation using the YOLOv8 model. Our research focuses on adding categories such as paper, metal, plastic, and others, utilizing the advanced object detection algorithm YOLOv8 for this purpose.
A Novel Approach to Fake News Detection Using Generative AI International Journal of Intelligent Systems and Applications in Engineering, 2024
Survey on Energy Generation Prediction for Offshore Wind Turbines Using Digital Twins Chaitanya P. Kale, Mahendra B. Gawali 2023 4th International Conference on Computation Automation and Knowledge Management Iccakm 2023, 2023 This article presents a comprehensive review of the technical advancements that have been made in offshore wind turbines via the use of digital twins. It discusses the digital twin architecture, which can anticipate and enhance turbine performance by using real-time data and predictive analytics. A digital twin is essentially a digital replica of a turbine. The study highlights how digital twins may assist improve the accuracy of energy output forecasting, save money on maintenance expenses, and raise the reliability of offshore wind energy systems. This paper investigates the intricate interactions that take place between virtual models and physical systems, illustrating how the combination of the two might lead to smarter and more environmentally friendly energy management.
Fault prediction model in wind turbines using deep learning structure with enhanced optimisation algorithm MB Gawali, SS Gawali, M Patil Journal of Control and Decision 12 (3), 471-488 , 2025 2025 Citations: 9
A conceptual framework for improving effectiveness of DevOps teams-An organizational systems perspective E Agbozo, MB Gawali AIP Conference Proceedings 3175 (1), 020086 , 2025 2025 Citations: 1
A systematic survey on machine learning classifier systems to address class imbalance NL Shelake, M Gawali 2024 Third International Conference on Artificial Intelligence … , 2024 2024 Citations: 1
A deep learning-based disease diagnosis with intrusion detection for a secured healthcare system SKR Kanna, MYB Murthy, MB Gawali, SM Rubai, NS Reddy, G Brammya, ... Knowledge and Information Systems 66 (9), 5669-5707 , 2024 2024 Citations: 16
Advancing offshore wind turbine energy generation prediction through comparative analysis and novel machine learning techniques CP Kale, MB Gawali 2024 IEEE International Conference on Smart Power Control and Renewable … , 2024 2024 Citations: 3
Predictive maintenance of server using machine learning and deep learning A njali Yeole J. Electrical Systems 20 (5s), 2828-2833 , 2024 2024 Citations: 6
A novel approach to fake news detection using generative AI M Patil, H Yadav, M Gawali, J Suryawanshi, J Patil, A Yeole, P Shetty, ... International Journal of Intelligent Systems and Applications in Engineering … , 2024 2024 Citations: 18
A novel human-to-robot interaction model based on transfer expert reinforcement learning with recurrent neural network MB Gawali, SS Gawali, M Patil, A Khandare Journal of Autonomous Intelligence 7 (2) , 2024 2024
Survey on Energy Generation Prediction for Offshore Wind Turbines Using Digital Twins CP Kale, MB Gawali 2023 4th International Conference on Computation, Automation and Knowledge … , 2023 2023 Citations: 2
Enhancing mobile multimedia trustworthiness through federated AI-based content authentication: enhancing mobile multimedia M Rajesh, K Vengatesan, R Sitharthan, SS Dhanabalan, MB Gawali Journal of Mobile Multimedia 19 (6), 1415-1437 , 2023 2023 Citations: 10
Optimization of Heterogeneous Task Scheduling in Cloud Computing SS Gawali, MB Gawali 2023 International Conference on Intelligent Systems for Communication, IoT … , 2023 2023 Citations: 4
Coffee Recommendation Using Machine Learning B Ketki, D Sakshi, H Prajakta, S Diksha, M Gawali International Journal of Innovative Research in Science, Engineering and … , 2022 2022
Cancer Detection using Machine Learning M Gawali, T Vaishnavi, W Prajakta, S Vaishnavi, S Akshay International Journal of Innovative Research in Science, Engineering and … , 2022 2022
Development of improved coyote optimization with deep neural network for intelligent skill knowledge transfer for human to robot interaction MB Gawali, SS Gawali International Journal of Intelligent Robotics and Applications 6 (2), 288-305 , 2022 2022 Citations: 11
Wireless Enterprise Resource Planning System for Micro, Small, Medium, Enterprises M Gawali, A Lodha, A Thorat, A Pawar, S Masane Journal of Web Development and Web Designing 6 (2), 26-39 , 2021 2021
Optimized skill knowledge transfer model using hybrid Chicken Swarm plus Deer Hunting Optimization for human to robot interaction MB Gawali, SS Gawali Knowledge-Based Systems 220, 106945 , 2021 2021 Citations: 21
iHuman CAPTCHA: An Alternative CAPTCHA for Visually Impaired Based on Face Liveness detection system M Gawali, Y Nanaware, A Kurhe, S Gade, S Shirode International Research Journal of Engineering and Technology 8 (05), 01-04 , 2021 2021
Sense Scheduling for Robotics Cognitive Intelligence MB Gawali, SS Gawali Evolution in Computational Intelligence: Frontiers in Intelligent Computing … , 2020 2020 Citations: 1
Disease Identification of Plant Leaf MMBG Mr. Vetal Shantanu, Mr. Pansare Jayram, Ms. Bhavsar Shweta, Ms. Kale Kamini Journal of VLSI Design and Signal Processing 6 (1), 5 , 2020 2020
Identification of Human Disease (Diabetic Retinopathy) using Convolutional Neural Network DMBG Ms. Akanksha Hon, Ms. Riya Shelke, Ms. Sharvari Hatekar, Ms. Mayuri Shelke Journal of Image Processing and Artificial Intelligence 6 (2), 5 , 2020 2020
MOST CITED SCHOLAR PUBLICATIONS
Task scheduling and resource allocation in cloud computing using a heuristic approach MB Gawali, SK Shinde Journal of Cloud Computing 7 (1), 4 , 2018 2018 Citations: 314
Standard deviation based modified cuckoo optimization algorithm for task scheduling to efficient resource allocation in cloud computing MB Gawali, SK Shinde J. Adv. Inf. Technol 8 (4) , 2017 2017 Citations: 38
Optimized skill knowledge transfer model using hybrid Chicken Swarm plus Deer Hunting Optimization for human to robot interaction MB Gawali, SS Gawali Knowledge-Based Systems 220, 106945 , 2021 2021 Citations: 21
A novel approach to fake news detection using generative AI M Patil, H Yadav, M Gawali, J Suryawanshi, J Patil, A Yeole, P Shetty, ... International Journal of Intelligent Systems and Applications in Engineering … , 2024 2024 Citations: 18
A deep learning-based disease diagnosis with intrusion detection for a secured healthcare system SKR Kanna, MYB Murthy, MB Gawali, SM Rubai, NS Reddy, G Brammya, ... Knowledge and Information Systems 66 (9), 5669-5707 , 2024 2024 Citations: 16
Development of improved coyote optimization with deep neural network for intelligent skill knowledge transfer for human to robot interaction MB Gawali, SS Gawali International Journal of Intelligent Robotics and Applications 6 (2), 288-305 , 2022 2022 Citations: 11
Enhancing mobile multimedia trustworthiness through federated AI-based content authentication: enhancing mobile multimedia M Rajesh, K Vengatesan, R Sitharthan, SS Dhanabalan, MB Gawali Journal of Mobile Multimedia 19 (6), 1415-1437 , 2023 2023 Citations: 10
Fault prediction model in wind turbines using deep learning structure with enhanced optimisation algorithm MB Gawali, SS Gawali, M Patil Journal of Control and Decision 12 (3), 471-488 , 2025 2025 Citations: 9
Implementation of IDEA, BATS, ARIMA and queuing model for task scheduling in cloud computing MB Gawali, SK Shinde 2016 Fifth International Conference on Eco-friendly Computing and … , 2016 2016 Citations: 7
Enhancement for data security in cloud computing environment MB Gawali, RB Wagh 2012 Nirma University International Conference on Engineering (NUiCONE), 1-6 , 2012 2012 Citations: 7
Predictive maintenance of server using machine learning and deep learning A njali Yeole J. Electrical Systems 20 (5s), 2828-2833 , 2024 2024 Citations: 6
Optimization of Heterogeneous Task Scheduling in Cloud Computing SS Gawali, MB Gawali 2023 International Conference on Intelligent Systems for Communication, IoT … , 2023 2023 Citations: 4
Advancing offshore wind turbine energy generation prediction through comparative analysis and novel machine learning techniques CP Kale, MB Gawali 2024 IEEE International Conference on Smart Power Control and Renewable … , 2024 2024 Citations: 3
Survey on Energy Generation Prediction for Offshore Wind Turbines Using Digital Twins CP Kale, MB Gawali 2023 4th International Conference on Computation, Automation and Knowledge … , 2023 2023 Citations: 2
A conceptual framework for improving effectiveness of DevOps teams-An organizational systems perspective E Agbozo, MB Gawali AIP Conference Proceedings 3175 (1), 020086 , 2025 2025 Citations: 1
A systematic survey on machine learning classifier systems to address class imbalance NL Shelake, M Gawali 2024 Third International Conference on Artificial Intelligence … , 2024 2024 Citations: 1
Sense Scheduling for Robotics Cognitive Intelligence MB Gawali, SS Gawali Evolution in Computational Intelligence: Frontiers in Intelligent Computing … , 2020 2020 Citations: 1
DCHEFT approach for task scheduling to efficient resource allocation in cloud computing MB Gawali, SK Shinde Int. J. Eng. Appl. Comput. Sci. 2 (9), 272-277 , 2017 2017 Citations: 1
Secured data outsourcing in cloud computing RN Kankrale, MB Gawali International Journal of Scientific and Research Publications , 2015 2015 Citations: 1
A novel human-to-robot interaction model based on transfer expert reinforcement learning with recurrent neural network MB Gawali, SS Gawali, M Patil, A Khandare Journal of Autonomous Intelligence 7 (2) , 2024 2024
