Hybrid Swarm Intelligence-Based Neural Framework for Optimizing Real-Time Computational Models in Engineering Systems Bhuvaneshwarri, M. Maheswari, C. Kalaivanan, P. Deepthi, Tatiraju V. Rajani Kanth, V. Saravanan International Journal of Computational and Experimental Science and Engineering, 2025 In modern engineering systems, real-time computational models are essential for optimizing performance, enhancing decision-making, and reducing latency in complex environments. This research presents a Hybrid Swarm Intelligence-Based Neural Framework (HSIN-F) to improve the efficiency, accuracy, and adaptability of real-time engineering computations. The proposed framework integrates Particle Swarm Optimization (PSO), Grey Wolf Optimizer (GWO), and Ant Colony Optimization (ACO) with a Deep Neural Network (DNN) to achieve a balance between exploration and exploitation, enabling optimal model parameter selection and reducing computational overhead. To validate the efficiency of HSIN-F, experiments were conducted across various real-time engineering applications, including industrial automation, smart grids, and IoT-based systems. The proposed model outperformed conventional optimization techniques in terms of processing speed, predictive accuracy, and system adaptability. Key performance metrics include: Prediction Accuracy: 98.2% (compared to 93.5% in traditional models), Computational Latency Reduction: 34.7%, Energy Efficiency Improvement: 27.5%, Error Rate Reduction: 32.1%. The hybrid swarm-based approach effectively adapts to dynamic changes in real-time scenarios, making it highly suitable for engineering applications requiring continuous optimization. Future research will explore hybrid metaheuristic strategies and federated learning-based decentralization to further enhance system performance and robustness.
Evolution-based Deployment with Efficient Routing and Crow Search Optimization in Internet of Things Application C. Kalaivanan, Ayman Amer, Maria Rubiston. M, M. Vennila, Jayant Giri, M. Dinesh Proceedings of the International Conference on Intelligent Computing and Control Systems Iciccs 2025, 2025 IoT technologies to bolster residential security, safety, and sustainability. By leveraging facial recognition for door access, enhancing fire safety monitoring, and integrating energy harvesting, it aims to create more resilient and eco-friendly residential environments. These innovations offer comprehensive solutions to address evolving challenges and optimize residential living. An ED Model coupled with Crow Search Optimization (CSO) for enhancing the efficiency and reliability of IoT applications. The ED model integrates static routing mechanisms with efficient protocols like AOMDV, ensuring robust connectivity and energy-efficient operation in diverse environments. Leveraging CSO, inspired by collective crow intelligence, enhances network performance by dynamically adapting to changing conditions. Through simulations and comprehensive analysis, the proposed approach demonstrates superior performance compared to existing models, achieving high data delivery ratio, network throughput, and energy efficiency. This integrated framework offers a sustainable solution for resilient IoT deployments, addressing evolving challenges and optimizing residential living environments.
Improvement of Power Quality by using TSK-Fuzzy Controllers in Wind and Photovoltaic based Hybrid Nanogrid Tarakanta Jena, C. Kalaivanan, B Eswararao, Suresh Kakinatla, Ankita Nainwal, G. Durgadevi, S. Vinod Reddy 2025 International Conference on Computing Technologies Icoct 2025, 2025 Nanogrid power systems are becoming more popular in present decade. Majority homes are facilitating with inverters for power backup during grid outages. These inverters can be able to operate as Nanogrid by integrating renewable energy sources along with proper control methodology. Hybrid wind power and photovoltaic (PV) generation units have been deployed on numerous rooftops globally, encompassing individual homes, apartment complexes, educational institutions, healthcare facilities, and small industrial operations. While these systems are linked to a single-phase grid, they incorporate a battery to provide backup power during instances of power failure. This setup has the potential to establish a Nanogrid for low-energy applications. The Nanogrid system accommodates a variety of loads, necessitating an efficient control strategy to ensure power quality and mitigate reactive power. By utilizing the inverter within the Nanogrid to counteract reactive power, the demand for reactive power from the main utility grid can be reduced. Individual MPPT devices are employed separately for wind and PV energy sources to enhance power generation efficiency. The Nanogrid system interfaces with the single-phase utility grid by regulating the inverter. To ensure optimal power quality, a dedicated control methodology has been designed to manage the inverter and maintain the voltage at their specified level. Proposed control methodology is designed by utilizing TSK-Fuzzy controllers to enhance the performance as compared with conventional PI controllers. Simulink package on MATLAB platform is employed to demonstrate the outcomes and evaluate the effectiveness of the suggested approach.
Enhancement of Power Quality by Novel Control Method of Wind-AE-FC-BSS Based Hybrid Microgrid Under Faults on Distribution Lines C. Kalaivanan, Putchakayala Yanna Reddy, Veera Nagi Reddy, Tellapati Anuradha Devi, Pareshwar Prasad, Thamizhkani. B, R Phani Vidyadhar, Burada Sankara Rao 2025 IEEE North East India International Energy Conversion Conference and Exhibition Ne Iecce 2025, 2025 Standalone electrical power generation systems that harness wind energy are widely employed across various models in multiple locations. To maintain a balance of power within these autonomous systems, the presence of batteries is crucial. Additionally, the combination of Electrolyzer and Fuel Cell (FC) has the potential to strengthen independent Microgrid systems, leading to increased dependability and decreased overall expenses. Normally, a three-legged inverter is used to provide AC power to various loads including single and three phase load units. However, distribution power lines often experience faults. Therefore, it is crucial to implement suitable control techniques on both the AC and DC sides to uphold power quality across different operational conditions. To ensure its longevity, the turbine speed cannot be restored after a malfunction takes place. Consequently, an updated Maximum Power Point Tracker (MPPT) controller is employed to ensure the wind system operates effectively during faults occurring on the distribution lines. Additionally, a novel inverter control technique is introduced to restrict the current flow in the inverter legs during a fault condition. This study showcases the results of MATLAB-Simulink simulations to validate the proposed approach.
AOA based Maximum Power Point Tracking of PV System under Partial Shading Conditions for Boost Converter Driven DC Motor S. Umamaheswari, Jithin Kumar IJ, C. Kalaivanan, M. Sai Veerraju, Vikrant Singh, Y Sukhi, Rishov Krishna Baruah, Kandi Bhanu Prakash 5th IEEE International Conference on Sustainable Energy and Future Electric Transportation Sefet 2025, 2025 Photovoltaic (PV) systems are utilizing for many applications including power supply to DC motor drive in the industries. While generating electricity for supplying motor, multiple PV modules need to be connected in the combination of series and parallel. Under this configuration few of modules may be affected by partial shading due to multiple reasons. The Perturb and Observe (P&O) method is commonly employed to identify the maximum power point on the nonlinear characteristics of the power versus voltage curve, thereby optimizing utilization. Unfortunately, general P&O method will be failed to reach global maximum power point (GMPP) under partial shading phenomenon due to existence of multiple local peaks. To avoid this issue, an optimization technique namely Addax Optimization Algorithm (AOA) is implemented to identify GMPP easily with fast and accurate. In order to drive the DC motor, a boost circuit is inserted between PV system and DC motor which is also forced to operate as maximum power point tracking (MPPT) device of the PV system by integrated proposed control method. The AOA+P&O methodology is integrated with the control of DC motor for generating required gating signals for the boost device to achieve the proposed control methodology. The proposed method is compared with Ant Colony Optimization (ACO), Modified Invasive Weed Optimization (MIWO) and Whale Inspired Optimization (WIO) to known the significance of proposed methodology. The system is developed in Hardware – in the – Loop (HIL) process on OPAL-RT platform to present various outcomes.
RETRACTION:A novel hyperparameter tuned deep learning model for power quality disturbance prediction in microgrids with attention based feature learning mechanism R. Dineshkumar, Anna Alphy, C. Kalaivanan, K. Bashkaran, Balachandra Pattanaik, T. Logeswaran, K. Saranya, Ganeshkumar Deivasikamani, A. Johny Renoald Journal of Intelligent and Fuzzy Systems, 2024 Microgrids (MGs) have become a reliable power source for supplying energy to rural areas in a secure, consistent, and low-carbon emission manner. Power quality disturbance (PQD) is a common issue that reduces the MGs networks’ reliability and restricts its usage on a small scale. The performance, reliability and lifetime of the various power devices can be affected due to the problem of PQD in the network. Researchers have proposed numerous PQD monitoring techniques based on artificial intelligence. However, they are limited to low margins and accuracy. So, this paper suggests a novel hyperparameter-tuned or optimized deep learning model with an attention-based feature learning mechanism for PQD prediction. The critical stages of the proposed work, such as data collection, feature extraction, and PQD prediction, are as follows. The PQD signals are first produced using the IEEE 1159 standard. Following that, the original time-domain features are directly recovered from the dataset, and the frequency-domain features using discrete wavelet transform (DWT). The extracted features were fed into visual geometry group 16 with multi-head attention and optimal hyperparameter-based bidirectional long short-term memory (V16MHA-OHBM) to perform spatial and temporal feature extraction. These extracted features are concatenated and given to the fully connected layer to forecast the PQD. The results showed that the suggested approach surpasses the prior state-of-the-art algorithms when trained and tested using 16 different types of synthetic noise PQD data produced using mathematical models in line with IEEE 1159.
Development of DPOS Algorithm by Integrating the IoT, Blockchain and AI to Reduce the Consumption of Energy M. Panneer Selvam, G. Karthikeyan, C. Kalaivanan, S Vijay Shankar 2024 2nd International Conference Computational and Characterization Techniques in Engineering and Sciences Ic3tes 2024, 2024 Current research has engrossed on the potential of the blockchain system to resolve security concerns in the IoT net. However, blockchain's intrinsic scalability problems become noticeable in environments with a high volume of data created by a significant number of Internet of Things (IoT) devices. In this work, researchers used an efficient consensus technique to overcome these challenges. For the management of data generated by the Internet of Things, we propose a scalable solution based on blockchain technology. This framework ensures enhanced efficiency and effectiveness in Internet of Things networks using constrained resources by using the delegation Proof of Stake (DPoS) consensus approach. To lessen the load on blockchain-based IoT networks, DPoS allows just a select group of chosen delegates to verify and approve transactions. To facilitate distributed storage, the investigators in this study constructed the Interplanetary File System (IPFS), and they also developed a Docker system to gauge net presentation in terms of latency, productivity, and source use. Distributed stored latency, throughput, utilisation of resources, and file upload length and speed were the four areas that researchers examined in our inquiry. Empirical results from researchers show that our approach has a minimal latency of less than 0.977 Ms the suggested method works better than Proof of Stake (PoS), which is considered to be the most advanced consensus method. Researchers further show that the suggested method might be helpful in Internet of Things applications that need to be resource-efficient or low latency.
Role of Renewable Energy in Sustainable Development C. Kalaivanan, M. Panneer Selvam, G. Karthikeyan, S Vijay Shankar 2024 2nd International Conference Computational and Characterization Techniques in Engineering and Sciences Ic3tes 2024, 2024
Design and implementation of advanced inverter control mechanisms to maximize hosting capacity in solar photovoltaic systems combined with battery energy storage P Kavitha, C Kalaivanan, BVS Acharyulu, YLN Rao Journal of Energy Storage 152, 120091 , 2026 2026 Citations: 1
Pelican Optimization Algorithm based Maximum Power Point Tracking of PV System under Partial Shading C Kalaivanan, GS Babu, V Shanmugasundaram, S Dangi, AA Kumar, ... 2026 International Conference on Electric Power and Renewable Energy (EPREC … , 2026 2026
Enhancing flexibility of combined energy system by renewable energy sources using hybrid LOA-MVGAN approach S Padhmanabhaiyappan, P Sabarish, C Kalaivanan, K Srilakshmi Renewable Energy 250, 123194 , 2025 2025 Citations: 6
AOA based Maximum Power Point Tracking of PV System under Partial Shading Conditions for Boost Converter Driven DC Motor S Umamaheswari, JK IJ, C Kalaivanan, MS Veerraju, V Singh, Y Sukhi, ... 2025 IEEE 5th International Conference on Sustainable Energy and Future … , 2025 2025
Enhancement of Power Quality by Novel Control Method of Wind-AE-FC-BSS Based Hybrid Microgrid Under Faults on Distribution Lines C Kalaivanan, PY Reddy, VN Reddy, TA Devi, P Prasad, RP Vidyadhar, ... 2025 IEEE North-East India International Energy Conversion Conference and … , 2025 2025
Improvement of Power Quality by using TSK-Fuzzy Controllers in Wind and Photovoltaic based Hybrid Nanogrid T Jena, C Kalaivanan, B Eswararao, S Kakinatla, A Nainwal, G Durgadevi, ... 2025 International Conference on Computing Technologies (ICOCT), 1-6 , 2025 2025 Citations: 7
Role of Renewable Energy in Sustainable Development C Kalaivanan, MP Selvam, G Karthikeyan, SV Shankar 2024 Second International Conference Computational and Characterization … , 2024 2024
Hybrid Deep Learning Models to Recognise the Solar Power Quality Distribution by Integrating Power System G Karthikeyan, C Kalaivanan, MP Selvam, SV Shankar 2024 Second International Conference Computational and Characterization … , 2024 2024
Development of DPOS Algorithm by Integrating the IoT, Blockchain and AI to Reduce the Consumption of Energy MP Selvam, G Karthikeyan, C Kalaivanan, SV Shankar 2024 Second International Conference Computational and Characterization … , 2024 2024 Citations: 1
Implementation of EEG signal decomposition and feature extraction through efficient wavelet transforms P Pavithara, C Kalaivanan, P Ponmurugan, VL Jothi, K Karthik, KK Kumar 2024 International Conference on Communication, Computing and Internet of … , 2024 2024 Citations: 3
HYBRID SWARM INTELLIGENCE-BASED NEURAL FRAMEWORK FOR OPTIMIZING REAL-TIME COMPUTATIONAL MODELS IN ENGINEERING SYSTEMS V TATIRAJU INTERNATIONAL JOURNAL 11 (1) , 2024 2024
Integration of Microgrid with Power for Supplying Quality Power of High Reliability and Efficiency C Kalaivanan, GK Kumar, N Sakthisaravanan, G Sajiv, V Mohanavel 2022 6th International Conference on Electronics, Communication and … , 2022 2022 Citations: 1
An Improved Network Segmentation Performance in Lesion Segmentation based on Mask R-CNN T Thivya, C Kalaivanan, N Juliet, GM Valantina, V Mohanavel 2022 6th International Conference on Electronics, Communication and … , 2022 2022 Citations: 3
An Efficient Object Detection and Classification from Restored Thermal Images based on Mask RCNN E Thenmozhi, A Karunakaran, JR Arunkumar, V Chinnammal, ... 2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile … , 2022 2022 Citations: 25
An efficient liver disease prediction based on deep convolutional neural network using biopsy images S Bharathi, A Balaji, C Kalaivanan, R Anusuya 2022 3rd International Conference on Smart Electronics and Communication … , 2022 2022 Citations: 4
Artificial Intelligence Based Cooling System For Managing The Energy Efficiency MSSDCKMRJEMSDTPDJ Gothania Journal of Contemporary Issues in Business and Government 27 (1), 1649-1659 , 2021 2021 Citations: 3
Partial Discharge Analysis Of Nanostructured Mineral Oil Under DC Voltages K Thamaraikani, S Chandrasekar, C Kalaivanan Turkish Journal of Computer and Mathematics Education 12 (9), 2859-2863 , 2021 2021
Design and Simulation of High Voltage Short Pulse Generator G Nithya, S Chandrasekar, C Kalaivanan, K Karpagavani Turkish Journal of Computer and Mathematics Education 12 (9), 2839-2847 , 2021 2021
Artificial Intelligence Based Cooling System For Managing The Energy Efficiency T Puyalnithi, J Gothania Journal of Contemporary Issues in Business and Government Vol 27 (1) , 2021 2021 Citations: 1
Design and development of extract maximum power from single-double diode PV model for different environmental condition using BAT optimization algorithm L Thangamuthu, JR Albert, K Chinnanan, Banu Journal of Intelligent & Fuzzy Systems, 1-12 , 2021 2021 Citations: 83
MOST CITED SCHOLAR PUBLICATIONS
Investigations on leakage current and phase angle characteristics of porcelain and polymeric insulator under contaminated conditions S Chandrasekar, C Kalaivanan, A Cavallini, GC Montanari IEEE Transactions on Dielectrics and Electrical Insulation 16 (2), 574-583 , 2009 2009 Citations: 189
Design and development of extract maximum power from single-double diode PV model for different environmental condition using BAT optimization algorithm L Thangamuthu, JR Albert, K Chinnanan, Banu Journal of Intelligent & Fuzzy Systems, 1-12 , 2021 2021 Citations: 83
Partial discharge detection as a tool to infer pollution severity of polymeric insulators S Chandrasekar, C Kalaivanan, GC Montanari, A Cavallini IEEE transactions on Dielectrics and Electrical Insulation 17 (1), 181-188 , 2010 2010 Citations: 68
An Efficient Object Detection and Classification from Restored Thermal Images based on Mask RCNN E Thenmozhi, A Karunakaran, JR Arunkumar, V Chinnammal, ... 2022 Sixth International Conference on I-SMAC (IoT in Social, Mobile … , 2022 2022 Citations: 25
Investigation of lightning impulse voltage characteristics and other thermo-physical characteristics of vegetable oils for power apparatus applications D Divakaran, C Kalaivanan 2012 IEEE 10th International Conference on the Properties and Applications … , 2012 2012 Citations: 21
A Study on the Influence of SiO 2 Nano Particles on the Failure of XLPE Underground Cables due to Electrical Treeing C Kalaivanan, S Chandrasekar Journal of Electrical Engineering & Technology 14 (6), 2447-2454 , 2019 2019 Citations: 14
Investigations on harmonic contents of leakage current of porcelain insulator under polluted conditions S Chandrasekar, C Kalaivanan Proceedings of Fifteenth National Power Systems Conference (NPSC), 340-344 , 2008 2008 Citations: 13
Investigations on flashover performance of porcelain insulators under contaminated conditions S Chandrasekar, K Krishnamoorthi, M Panneerselvam, C Kalaivanan National Conf. Electrical Engineering and Embedded Systems,(NCEEE), 112-116 , 2008 2008 Citations: 12
Improvement of Power Quality by using TSK-Fuzzy Controllers in Wind and Photovoltaic based Hybrid Nanogrid T Jena, C Kalaivanan, B Eswararao, S Kakinatla, A Nainwal, G Durgadevi, ... 2025 International Conference on Computing Technologies (ICOCT), 1-6 , 2025 2025 Citations: 7
Study on pollution severity of porcelain insulators using LC and phase angle measurement S Chandrasekar, C Kalaivanan, S Karthikeyan 2008 IEEE Region 10 and the Third international Conference on Industrial and … , 2008 2008 Citations: 7
Enhancing flexibility of combined energy system by renewable energy sources using hybrid LOA-MVGAN approach S Padhmanabhaiyappan, P Sabarish, C Kalaivanan, K Srilakshmi Renewable Energy 250, 123194 , 2025 2025 Citations: 6
Analysis of electrical tree inception and propagation in XLPE nano-composites C Kalaivanan, S Chandrasekar Asian Journal of Research in Social Sciences and Humanities 6 (8), 1913-1922 , 2016 2016 Citations: 5
An efficient liver disease prediction based on deep convolutional neural network using biopsy images S Bharathi, A Balaji, C Kalaivanan, R Anusuya 2022 3rd International Conference on Smart Electronics and Communication … , 2022 2022 Citations: 4
Andrea Cavallini and Gian Carlo Montanari,“Investigations on Leakage Current and Phase Angle Characteristics of Porcelain and Polymeric Insulator under Contaminated Conditions” S Chandrasekar, C Kalaivanan IEEE Trans. Dielectrics and Electr. Insul 16 (2), 574-583 , 2009 2009 Citations: 4
Implementation of EEG signal decomposition and feature extraction through efficient wavelet transforms P Pavithara, C Kalaivanan, P Ponmurugan, VL Jothi, K Karthik, KK Kumar 2024 International Conference on Communication, Computing and Internet of … , 2024 2024 Citations: 3
An Improved Network Segmentation Performance in Lesion Segmentation based on Mask R-CNN T Thivya, C Kalaivanan, N Juliet, GM Valantina, V Mohanavel 2022 6th International Conference on Electronics, Communication and … , 2022 2022 Citations: 3
Artificial Intelligence Based Cooling System For Managing The Energy Efficiency MSSDCKMRJEMSDTPDJ Gothania Journal of Contemporary Issues in Business and Government 27 (1), 1649-1659 , 2021 2021 Citations: 3
Understanding inception and propagation of electrical tree discharge characteristics in xlpe nano-composites C Kalaivananand, S Chandrasekar Power Research-A Journal of CPRI, 111-116 , 2017 2017 Citations: 2
Design and implementation of advanced inverter control mechanisms to maximize hosting capacity in solar photovoltaic systems combined with battery energy storage P Kavitha, C Kalaivanan, BVS Acharyulu, YLN Rao Journal of Energy Storage 152, 120091 , 2026 2026 Citations: 1
Development of DPOS Algorithm by Integrating the IoT, Blockchain and AI to Reduce the Consumption of Energy MP Selvam, G Karthikeyan, C Kalaivanan, SV Shankar 2024 Second International Conference Computational and Characterization … , 2024 2024 Citations: 1
