Artificial Intelligence, Control and Systems Engineering, Electrical and Electronic Engineering
17
Scopus Publications
281
Scholar Citations
6
Scholar h-index
4
Scholar i10-index
Scopus Publications
Performance of Kinetic Models on Prediction of Biogas From Food Waste With/Without Pretreatment Cherukuri Nithin Raja, Manju Asokkumar, Purushothaman Parthasarathy Chemical Engineering and Technology, 2026 This study assesses the performance of different kinetic models for predicting biogas yield from anaerobic digestion (AD) and co‐digestion of food wastes (FWs) with/without garden waste under different pretreatment scenarios (thermal, extrusion, and sequential). Results show that cone and hydrolysis constant increase, whereas lag phase decrease in pretreated FW, indicating enhanced hydrolysis and faster biodegradability exhibiting better performance. On other hand, MFW/MFGW shows opposite trend due to its complex nature. Modified logistic showed better performance in all samples and CM in MFW/MFGW. Despite its better performance, superimposed exhibited inaccuracy in biogas yield. In conclusion, kinetic models enhance understanding the performance of AD of samples studied under various pretreated conditions.
Analysis for Density of Bands bulk using Silicon uniaxial strain and Gallium arsenide biaxial strain by varying the energy in HEMTs for High Power gain Manju A, Anbuselvan N, Anandan P 10th International Conference on Electrical Energy Systems Icees 2024, 2024 The goal is to analyse the density of bands bulk using Silicon uniaxial and Gallium arsenide biaxial strain by varying the energy in High Electron Mobility Transistor HEMT. Two optimization techniques are employed uniaxial silicon and biaxial strain gallium arsenide and are correlated to enhance density through barrier layer energy variations. The total density will be increased by variation of the energy in uniaxial silicon and biaxial strain gallium arsenide for samples studied for 2400. The silicon uniaxial strain technique’s total energy is compared to the gallium arsenide biaxial strain at mid-point of polarity of positive and negative at the resultant value 38eV. The value of N analysis for the samples around 2400 is statistics - 2 t test is considered to be statistically significant. From the above analysis it is identified how the impact of that silicon uniaxial technique and the gallium arsenide biaxial strain plays a vital role in the improvement of total energy of different strains for improving density.
IoT and Cloud-Based Smart Farming with Optimized Convolutional Neural Networks for Grape Fruit Disease Classification N Anbuselvan, A Manju, P Anandan 2023 International Conference on Data Science Agents and Artificial Intelligence Icdsaai 2023, 2023 The importance of agriculture as a component of India’s economy is well-known. Also, most people agree that a big segment of the population relies on agriculture as a source of income. More over 60% of the population is connected to agriculture in some way, shape, or form. More recently, technological advancements have allowed for the application of IoTtechnology in agriculture, which has increased production while decreasing resource waste. This paper presents a novel model for Smart Farming that leverages the IoT technology. The model incorporates an enhanced crow search (ECS) algorithm to effectively optimise parameters for a multilevel feature selection algorithm. The ECS-CNN technique is a feature selection algorithm that has been specifically developed for the purpose of enhancing the performance of a convolutional neural network (CNN) classifier. The methodology proposed entails the initial acquisition of plant images using IoT devices, which are subsequently stored in a cloud-based system. The ECS-CNN model, which has been proposed, is deployed on a cloud platform for the purpose of detecting and categorising instances of plant diseases. The present study employs a benchmark dataset known as the Grape Image Gallery dataset for the purpose of conducting experiments.
Classification of Massive Data Sets Using a Revolutionary Grey Wolf Optimization Algorithm and a Deep Learning Model in a Cloud-Based Setting P Anandan, A Manju, Murthy Ravaleedhar Reddy 2023 International Conference on Data Science Agents and Artificial Intelligence Icdsaai 2023, 2023 The field of big data analytics has attracted a considerable amount of attention in the realm of academic research due to the fact that it is incredibly useful in a wide variety of real-time applications. This is the reason why the subject has received so much attention. The relatively recent development of machine learning and deep learning models has resulted in an improvement in performance. This improvement has been brought about as a result of the development of these models. The application of these models to the study of massive datasets has become much simpler as a result of these models, which has led to an improvement in performance outcomes. When considering the complexity of large data and the processing requirements that it imposes, it is beneficial to employ feature selection strategies that make use of metaheuristic optimization algorithms. This is due to the fact that big data is distinguished by the vast quantity of information that it contains. There is a huge advantage in the fact that these algorithms are able to successfully uncover the best potential set of features, which ultimately results in improved classification performance. In this particular piece of literature, a new approach that is known as the GWOA-DBN model is presented as a solution to the problem. In order to construct this model and the benefits that come along with it, the Grey Wolf Optimization algorithm and the optimal deep belief network have been coupled. The objective of the Apache Spark environment is to find a solution to the problem of classifying enormous volumes of data. This is the goal of the environment, which is the ultimate objective of the environment. The GWOA-DBN technique, which involves the construction of a feature selection method, is built on the base of the Grey Wolf Optimization Algorithm (GWOA), which acts as the cornerstone for the methodology. In the process of utilizing this strategy, the goal is to determine which subset of traits is the most ideal. The DBN-based classification model is also applied in order to appropriately categorize the large amounts of data into the precise categories that are necessary. This is done in order to fulfill the requirements. We aim to get the best possible results. The efficient processing of enormous data sets is another goal of using the Apache Spark platform. In order to provide the most optimal outcomes, this is carried out. This takes place in addition to the purpose that was specified earlier. A number of tests were carried out in an effort to improve the efficiency of the GWOA-DBN method on the whole. As a result of the results of these studies, it was proved that this method is more effective than other approaches.
Optimal integration of capacitor and distributed generation in distribution system considering load variation using bat optimization algorithm Thangaraj Yuvaraj, Kaliaperumal Rukmani Devabalaji, Natarajan Prabaharan, Hassan Haes Alhelou, Asokkumar Manju, Poushali Pal, Pierluigi Siano Energies, 2021 In this article, an efficient long-term novel scheduling technique is proposed for allocating capacitors in a combined system involving distributed generation (DG) along with radial distribution systems (RDS). We introduce a unique multi-objective function that focuses on the reduction of power loss with the maximization of voltage stability index (VSI) subjected to constraints of equality and inequality systems. Loss sensitivity factor and VSI together are involved in pre-identifying the locations of capacitors and DG. Determination of the optimal size of capacitor and DG is performed by utilizing the Bat algorithm (BA) for all the loads in RDS. The conventional approach considers the medium load of (1.0) condition generally, but the proposed method changes the feeder loads linearly, ranging from light load (0.5) to peak load (1.6) with the value of step size as 1%. BA determines the optimal size of the capacitor and DG for each step load. The curve fitting technique is used for deducing the generalized equation of capacitor size and DG for all conditions of the load with the various loading condition sized by distributed network operators (DNOs). Further, various load models such as industrial, residential, and commercial loads have been considered to show the efficiency of the present approach. Validation of results is performed in different scenarios on a 69-bus test system and on a standard IEEE 33-bus system. The results exhibit improved accuracy with less power loss value, superior bus voltage, and stability of system voltage with a higher rate of convergence.
Optimal Allocation of DG units to Counteract Load Growth K Narayanan., R Girish Ganesan., A Manju. International Conference on Innovative Smart Grid Technologies Isgt Asia 2018, 2018 With the emergence of various Distributed Generation (DG) Units, the modern power system has undergone massive structural changes. The increase in system load is a gradual and inevitable process over time. This leads to increase in the system losses. The effect of increase in system load can be counteracted by the presence of optimally allocated DG units and can also defer further investment of reinforcement in the system. In this paper, the DG allocation is performed by Genetic Algorithm (GA) method in two-steps. The main objectives of DG allocation in this paper has been considered as (i) a single objective namely Loss Minimization and (ii) a multi-objective function namely Maximizing Voltage Stability margin and Loss minimization. Economic analysis on contribution of each factor towards the cost of energy over a period of seven years is performed. Such analysis gives an idea to the system planner, in calculating the breakeven point and investment on reinforcement. The results obtained for the standard IEEE 33 bus radial distribution system have been presented, giving a promising insight for future investments.
Voltage Lift Based Interleaved Flyback Converter Girish Ganesan R., Srividhya Pattabiraman, Narayanan K., Manju A. International Conference on Innovative Smart Grid Technologies Isgt Asia 2018, 2018 Conventional converters provide gain at the cost of high duty ratio operation, increased switch stress, increased control complexity and lossy power conversion. A non-isolated high gain DC-DC converter with two interleaved flyback stages is presented. The interleaved stage adopts a voltage lift capacitor to enhance the output voltage in the base stage of the converter. The secondary state consists of the secondary windings of the inductor in series to the output of the primary stage. This arrangement provides high gain without extreme duty ratio operation. The simulation results for a design of 100W, 24V/480V is presented which validate the feasibility of the proposed converter. This converter is a proposed to be used as a viable alternative in HID lamp and automobile applications. The hardware verification of the proposed converter is underway.
A computational approach of highly secure hash algorithm for color image steganography using edge detection and honey encryption algorithm International Journal of Engineering and Technology Uae, 2018
A survey on implementation of recent reversible watermarking techniques in medical images and other applications Journal of Advanced Research in Dynamical and Control Systems, 2018
Analysis for Density of Bands bulk using Silicon uniaxial strain and Gallium arsenide biaxial strain by varying the energy in HEMTs for High Power gain A Manju, N Anbuselvan, P Anandan 2024 10th International Conference on Electrical Energy Systems (ICEES), 1-4 , 2024 2024
IoT and Cloud-Based Smart Farming with Optimized Convolutional Neural Networks for Grape Fruit Disease Classification N Anbuselvan, A Manju, P Anandan 2023 International Conference on Data Science, Agents & Artificial … , 2023 2023 Citations: 1
Classification of massive data sets using a revolutionary grey wolf optimization algorithm and a deep learning model in a cloud-based setting P Anandan, A Manju, MR Reddy 2023 International Conference on Data Science, Agents & Artificial … , 2023 2023 Citations: 1
Optimal integration of capacitor and distributed generation in distribution system considering load variation using bat optimization algorithm T Yuvaraj, KR Devabalaji, N Prabaharan, H Haes Alhelou, A Manju, P Pal, ... Energies 14 (12), 3548 , 2021 2021 Citations: 63
Support Vector Machine Algorithm with Probabilistic Neural Network Based Brain Tumor Detection and Classification System P Anandan, N Anbuselvan, A Manju, S Manjula Journal of Computational and Theoretical Nanoscience 18 (3), 922-928 , 2021 2021 Citations: 1
Bioavailability and Risk Assessment of Trace Metals in Sediments of a high altitude eutrophic lake, Ooty, Tamil Nadu, India SKS Purushothaman P, Manju A, Rajesh Kumar Ranjan Environmental Science and Pollution research 28 (15), 18616-18631 , 2020 2020
Voltage lift based interleaved flyback converter S Pattabiraman, K Narayanan, A Manju 2018 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), 214-219 , 2018 2018 Citations: 1
Optimal allocation of dg units to counteract load growth K Narayanan, RG Ganesan, A Manju 2018 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), 1-6 , 2018 2018 Citations: 6
A computational approach of highly secure hash algorithm for color image steganography using edge detection and honey encryption algorithm K Dhanasekaran, P Anandan, A Manju International Journal of Engineering & Technology 7 (2.24), 239-242 , 2018 2018 Citations: 13
Tuning of Type 2 Fuzzy in Magnetic Levitation System to meet position constraints T Vinusha, A Manju International Journal of Applied Engineering Research 10 (36), 27802-27807 , 2015 2015
Traffic Light Controller Based On Fuzzy Logic PR Anju, A Manju International Journal of Applied Engineering Research 10 (36), 27792-27801 , 2015 2015
Energy Comparative Study Analysis of Three MPPT Techniques For Photo Voltaic System K Madhavan, A Manju, M Venkatesh kumar International Journal of Applied Engineering Research 10 (36), 27792-27796 , 2015 2015
Solar MPPT Using Fuzzy Controller Optimized By Genetic Algorithm RV Jayasri, A Manju, M Venkateshkumar International Journal of Applied Engineering Research 10 (36), 27786-2779 , 2015 2015
Neuro Fuzzy Based Power Management For Hybrid Renewable Energy Source A Manju, G Banupriya, M Venkateshkumar International Journal of Applied Engineering Research 10 (4), 3751-3755 , 2015 2015
Diagnosis of Glaucoma Based on Cup To Disc Ratio From Digital Fundus Images A Manju, A Rubiya International Journal of Applied Engineering Research 10 (4), 3490-3493 , 2015 2015
Automatic detection of diabetic Retinopathy based on color segmentation A manju, D Kamalapriya advances in natural and applied sciences 9 (6), 627-632 , 2015 2015 Citations: 1
Rule weight tuned fuzzy controller for robot manipulator using quantum inspired firefly algorithm A Manju, A Monasubramaniam Power Electronics and Renewable Energy Systems: Proceedings of ICPERES 2014 … , 2014 2014 Citations: 2
An improved quantum inspired firefly algorithm with interpolation operator A Manju, MJ Nigam Proceedings of the Third International Conference on Soft Computing for … , 2014 2014 Citations: 2
Application of exponential atmosphere concept in improving Firefly Algorithm A Manju, MJ Nigam Third International Conference on Computing Communication & Networking … , 2012 2012 Citations: 4
Firefly Algorithm with fireflies having quantum behavior A Manju, MJ Nigam International Conference on Radar, Communication and Computing (ICRCC), 2012 … , 2012 2012 Citations: 14
MOST CITED SCHOLAR PUBLICATIONS
Applications of quantum inspired computational intelligence: a survey A Manju, MJ Nigam Artificial Intelligence Review , 2012 2012.0 Citations: 156
Optimal integration of capacitor and distributed generation in distribution system considering load variation using bat optimization algorithm T Yuvaraj, KR Devabalaji, N Prabaharan, H Haes Alhelou, A Manju, P Pal, ... Energies 14 (12), 3548 , 2021 2021.0 Citations: 63
Firefly Algorithm with fireflies having quantum behavior A Manju, MJ Nigam International Conference on Radar, Communication and Computing (ICRCC), 2012 … , 2012 2012.0 Citations: 14
A computational approach of highly secure hash algorithm for color image steganography using edge detection and honey encryption algorithm K Dhanasekaran, P Anandan, A Manju International Journal of Engineering & Technology 7 (2.24), 239-242 , 2018 2018.0 Citations: 13
The Survey to Implement Recent Reversible Watermarking Techniques In Medical Images And Other Applications B Senthilraja, P Anandan, A Manju Journal of Advanced Research in Dynamical & Control Systems 10 , 0 Citations: 8
Optimal allocation of dg units to counteract load growth K Narayanan, RG Ganesan, A Manju 2018 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), 1-6 , 2018 2018.0 Citations: 6
A Study of parameter tuning of weighted fuzzy rule base using genetic algorithm for trajectory control of PUMA 560 M Subramaniam, A Manju, J Nigamc International Journal of Engineering Science and Technology (IJEST) 3 (9 … , 2011 2011.0 Citations: 6
Application of exponential atmosphere concept in improving Firefly Algorithm A Manju, MJ Nigam Third International Conference on Computing Communication & Networking … , 2012 2012.0 Citations: 4
Rule weight tuned fuzzy controller for robot manipulator using quantum inspired firefly algorithm A Manju, A Monasubramaniam Power Electronics and Renewable Energy Systems: Proceedings of ICPERES 2014 … , 2014 2014.0 Citations: 2
An improved quantum inspired firefly algorithm with interpolation operator A Manju, MJ Nigam Proceedings of the Third International Conference on Soft Computing for … , 2014 2014.0 Citations: 2
IoT and Cloud-Based Smart Farming with Optimized Convolutional Neural Networks for Grape Fruit Disease Classification N Anbuselvan, A Manju, P Anandan 2023 International Conference on Data Science, Agents & Artificial … , 2023 2023.0 Citations: 1
Classification of massive data sets using a revolutionary grey wolf optimization algorithm and a deep learning model in a cloud-based setting P Anandan, A Manju, MR Reddy 2023 International Conference on Data Science, Agents & Artificial … , 2023 2023.0 Citations: 1
Support Vector Machine Algorithm with Probabilistic Neural Network Based Brain Tumor Detection and Classification System P Anandan, N Anbuselvan, A Manju, S Manjula Journal of Computational and Theoretical Nanoscience 18 (3), 922-928 , 2021 2021.0 Citations: 1
Voltage lift based interleaved flyback converter S Pattabiraman, K Narayanan, A Manju 2018 IEEE Innovative Smart Grid Technologies-Asia (ISGT Asia), 214-219 , 2018 2018.0 Citations: 1
Automatic detection of diabetic Retinopathy based on color segmentation A manju, D Kamalapriya advances in natural and applied sciences 9 (6), 627-632 , 2015 2015.0 Citations: 1
A Novel Stochastic Algorithm Using Pythagorean Means for Minimization AM Subramaniam, A Manju, MJ Nigam Intelligent Control and Automation 1 (2), 82 , 2010 2010.0 Citations: 1
Bi-variate polynomial approximation of fuzzy controller using genetic algorithm for trajectory control of PUMA560 A Mona Subramaniam, A Manju, MJ Nigam International Conference on Advances in Information and Communication … , 2010 2010.0 Citations: 1
Analysis for Density of Bands bulk using Silicon uniaxial strain and Gallium arsenide biaxial strain by varying the energy in HEMTs for High Power gain A Manju, N Anbuselvan, P Anandan 2024 10th International Conference on Electrical Energy Systems (ICEES), 1-4 , 2024 2024.0
Bioavailability and Risk Assessment of Trace Metals in Sediments of a high altitude eutrophic lake, Ooty, Tamil Nadu, India SKS Purushothaman P, Manju A, Rajesh Kumar Ranjan Environmental Science and Pollution research 28 (15), 18616-18631 , 2020 2020.0
Tuning of Type 2 Fuzzy in Magnetic Levitation System to meet position constraints T Vinusha, A Manju International Journal of Applied Engineering Research 10 (36), 27802-27807 , 2015 2015.0
