Amit kumar Baburao Ranit

@prmceam.ac.in

Assistant Professor Civil Engineering
Prof Ram Meghe College of Engineering & Management

Amit kumar Baburao Ranit


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https://researchid.co/amitranit

RESEARCH INTERESTS

Hydraulics and Water Resources Engineering, GIS
15

Scopus Publications

106

Scholar Citations

5

Scholar h-index

3

Scholar i10-index

Scopus Publications

  • Review of Bayesian Approaches for Structural Integrity Assessment and Damage Identification
    Pradeep Bhadauria, A. B. Ranit, P. S. Chaudhary, K. A. Dongre, Shrikant M. Harle, A. P. Bhagat
    Operations Research Forum, 2026
  • Reducing Carbon Footprint in the Construction Industry: Strategies from Design to Operation
    Shrikant M. Harle, A. B. Ranit, Swati Ambadkar, S. Bejalwar
    Environmental Footprints and Eco Design of Products and Processes, 2026
  • Neural networks, CNNs, and hybrid models in structural retrofitting: a deep learning perspective
    Pradeep K. S. Bhadauria, Nilesh Zanjad, Sanket Gajanan Kalamkar, Amitkumar Ranit, Pravin Chaudhary
    Asian Journal of Civil Engineering, 2025
  • Machine learning and optimization in hybrid energy storage systems: Integrating MPC, PSO, MILP, and ANN for grid stability and efficiency
    Rajesh M. Bhagat, Dilendra B. Jasutkar, Amitkumar B. Ranit, Vikrant S. Vairagade, Balram Yelamasetti, Sagar D. Shelare, Shubham Sharma, Abinash Mahapatro, V.K. Bupesh Raja, Quadri Noorulhasan Naveed, Naoufel Kraiem, Saiful Islam, Jasmina Lozanovic
    International Journal of Electrical Power and Energy Systems, 2025
    • MPC reduces energy loss by 15% and boosts grid stability by 20%. • PSO cuts system costs by 12% and improves energy efficiency by 10%. • MILP lowers operational costs by 18% and enhances efficiency by 15%. • ANN hits 95% accuracy; hybrid storage boosts grid with renewables. Hybrid Energy Storage Systems (HESS) can provide solutions for grid stability and integration of renewable energy sources. A novel model integrating Model Predictive Control (MPC), Particle Swarm Optimization (PSO), Mixed-Integer Linear Programming (MILP), and Artificial Neural Networks (ANN) is developed to optimize HESS performance. MPC is employed for its predictive capabilities, enabling real-time control under dynamic grid conditions, while PSO optimizes system configurations for cost and efficiency. In the real-time operations of the grid, the MPC framework successfully handles complicated constraints with the possibility of being adaptively predictive. PSO optimizes the system by obtaining optimal configurations in non-linear and multimodal conditions with balanced cost and performance. MILP ensures the operating strategy of the system by fulfilling capacity, efficiency, and stability conditions at the grid level. ANN provides high precision predictions for energy management, hence enhancing the process of decision making for various cases. Simulations show up to 15.8% reductions in energy losses, 21.4% enhancements in grid stability, and 90% improvements in the operation efficiency as compared to the current methods. The integration benefits highlight superior adaptability and cost effectiveness. System costs are reduced to $1.6 million. Conclusion scalable pathway for enhancing renewable energy penetration and addressing the demands of the grid. The proposed model, employing advanced control and optimization techniques, ensures resilient energy systems capable of assimilating various REs and dynamic grid conditions that ensure proper transition towards low-carbon energy grids.
  • Impact of Shear Wall Placement on Seismic Performance of Vertically Irregular Structures
    Shrikant M. Harle
    Jordan Journal of Civil Engineering, 2025
    This study investigates the dynamic behavior of buildings under various structural configurations, offering insights into optimizing design for seismic resilience and structural stability. Using the STAAD-PRO software, a comprehensive analysis of 96 distinct building models was conducted to explore load distribution, stress allocation, and overall structural integrity. The research focused on the impact of building height and shear wall placement on critical parameters, such as frequency, period, and story shear. The findings reveal that for buildings measuring 18 meters in height, the highest frequency is achieved when the shear wall is positioned exclusively at the front. Conversely, taller structures, such as those at 45 meters, exhibit prolonged oscillation cycles when shear walls are placed at the front, back, and both sides. Story shear analysis further highlights that the highest values occur with shear walls strategically placed at these same locations. Notably, the 18-meter structure demonstrates the highest sensitivity to lateral forces, with a clear trend of decreasing story shear as building height increases. The study also uncovers a strong correlation between building height and displacement. As height increases, so does structural displacement; however, configurations with shear walls at the front, back, and both sides effectively minimize this movement. In conclusion, this research underscores the complex interplay between shear wall placement, building height, and structural responses. These findings provide valuable guidance for enhancing earthquake resistance, optimizing structural designs, and informing engineering decisions in building design and construction.
  • Development of an AI-Based System for an Ancient Character Extraction and Transformation: The Tipitaka Image Dataset of Pali Manuscript Characters
    S. R. Gudadhe, A. A. Bardekar, A. B. Ranit
    Lecture Notes in Electrical Engineering, 2025
  • Enhancing Pali Manuscript Interpretation with Artificial Neural Network Techniques
    Sangita Gudadhe, Aashish Bardekar, Amitkumar Ranit
    Lecture Notes in Networks and Systems, 2025
  • Structural Performance of LGS and Ferrocement Composite Element
    Arpana Akarte, Achal Gathe, Shrikant Harle, Amitkumar B. Ranit, Milind V. Mohod, Swati S. Nibhorkar
    Lecture Notes in Civil Engineering, 2025
  • Innovative approaches to fire-resistant building materials: a review
    P. K. S. Bhadauria, A. B. Ranit, P. S. Chaudhary, K. A. Dongre, Shrikant M. Harle, A. P. Bhagat
    Life Cycle Reliability and Safety Engineering, 2025
  • A Novel Approach using Machine Learning and NLP for Revolutionizing Pali Manuscript Conservation
    Sangita R. Gudadhe, Aashish A. Bardekar, Amitkumar B. Ranit
    4th International Conference on Sustainable Expert Systems Icses 2024 Proceedings, 2024
    The preservation and analysis of ancient Pali manuscripts are crucial for understanding India's cultural heritage. However, the unique shapes of Pali characters present significant challenges for accurate identification and classification. This research proposes a novel system that utilizes machine learning, image processing, and natural language processing (NLP) to convert Pali characters into understandable formats and decipher the Pali Prakrit language. By combining computer science and linguistics, the proposed model aims to effectively extract data from Pali literature. The proposed model was validated using the Government of India dataset, demonstrating improved character recognition accuracy and reduced memory footprint. This research contributes to the preservation of ancient Pali manuscripts and facilitates the study and understanding of this valuable cultural heritage.
  • A Novel Approach for Translating Kharosthi Script Text Into Pali Language
    Sangita Gudadhe, Aashish Bardekar, Amitkumar Ranit
    2024 IEEE 2nd International Conference on Emerging Trends in Engineering and Medical Sciences Icetems 2024, 2024
  • Investigation of Mechanical Behavior of Steel Fiber-Reinforced Geopolymer Concrete Under Multi-Axial Stress Conditions
    A.B. Ranit, N.S. Futane, V.R. Dhawale, S.M. Dhawade, R.S. Ingalkar, S.M. Harle
    Advances in Transdisciplinary Engineering, 2024
  • Flood Forecasting by Using Machine Learning
    Amitkumar Baburao Ranit, P. V. Durge
    Proceedings of the 4th International Conference on Communication and Electronics Systems Icces 2019, 2019
  • Techniques of Flood Forecasting and Their Applications
    Amitkumar Ranit, P. V. Durge
    Lecture Notes on Data Engineering and Communications Technologies, 2019
  • Different Techniques of Flood Forecasting and Their Applications
    Amitkumar B. Ranit, P.V. Durge
    Proceedings of the 2018 3rd IEEE International Conference on Research in Intelligent and Computing in Engineering Rice 2018, 2018

RECENT SCHOLAR PUBLICATIONS

  • Review of Bayesian Approaches for Structural Integrity Assessment and Damage Identification
    P Bhadauria, AB Ranit, PS Chaudhary, KA Dongre, SM Harle, AP Bhagat
    Operations Research Forum 7 (1), 8 , 2026
    2026
    Citations: 1
  • Reducing Carbon Footprint in the Construction Industry: Strategies from Design to Operation
    SM Harle, AB Ranit, S Ambadkar, S Bejalwar
    Reduction of Industrial Carbon Footprint, 43-91 , 2026
    2026
  • AI-driven sustainable concrete mix design: Hybrid deep Q-Learning and genetic algorithms-based multi-objective machine learning optimizations for high structural strength, low …
    EESM Amruta A. Yadav a , Sneha G. Hirekhan a , Pranita S. Bhandari b ...
    Structures 82 , 2025
    2025
    Citations: 5
  • Neural networks, cnns, and hybrid models in structural retrofitting: a deep learning perspective
    PKS Bhadauria, N Zanjad, SG Kalamkar, A Ranit, P Chaudhary
    Asian Journal of Civil Engineering 26 (11), 4499-4516 , 2025
    2025
    Citations: 2
  • Tailoring the pore structure of mesoporous composite agro‑based adsorbents for the enhanced removal of Cu(II) and Ni(II) heavy metal ions from wastewater
    RM Bhagat, SR Khandeshwar, AB Ranit, MP Bhorkar, BP Nandurkar, ...
    Clean Technologies and Environmental Policy , 2025
    2025
    Citations: 2
  • Innovative approaches to fire-resistant building materials: a review
    PKS Bhadauria, AB Ranit, PS Chaudhary, KA Dongre, SM Harle, ...
    Life Cycle Reliability and Safety Engineering, 1-14 , 2025
    2025
    Citations: 1
  • Neural networks, CNNs, and hybrid models in structural retrofitting: a deep learning perspective
    ARPC Pradeep K. S. Bhadauria, Nilesh Zanjad, Sanket Gajanan Kalamkar
    Asian Journal of Civil Engineering Building and Housing , 2025
    2025
  • Machine learning and optimization in hybrid energy storage systems: Integrating MPC, PSO, MILP, and ANN for grid stability and efficiency
    JL Rajesh M. Bhagat, Dilendra B. Jasutkar, Amitkumar B. Ranit, Vikrant S ...
    International Journal of Electrical Power & Energy Systems 170, 1-16 , 2025
    2025
    Citations: 7
  • GREEN BUILDING PROJECT MANAGEMENT APPROACH IN CONSTRUCTION PHASES
    DABR Aachal Bhaurao Kore
    DASTAVEJ RESEARCH JOURNAL 55 (1), 12-17 , 2025
    2025
  • Impact of Shear Wall Placement on Seismic Performance of Vertically Irregular Structures
    SGT Shrikant M. Harle, Amitkumar B. Ranit, Pravin Shankarrao Choudhary ...
    Jordan Journal of Civil Engineering 19 (2), 211-229 , 2025
    2025
  • CLASH DETECTION IN CONSTRUCTION PROJECT BY BIM
    RRW Mr. Akash Mahendra Ingle, Dr. Amitkumar B. Ranit
    DASTAVEJ RESEARCH JOURNAL 54 (12) , 2025
    2025
  • A Novel Approach for Translating Kharosthi Script Text Into Pali Language
    S Gudadhe, A Bardekar, A Ranit
    2024 2nd International Conference on Emerging Trends in Engineering and … , 2024
    2024
  • A novel approach using machine learning and NLP for revolutionizing Pali manuscript conservation
    SR Gudadhe, AA Bardekar, AB Ranit
    2024 4th International Conference on Sustainable Expert Systems (ICSES), 844-848 , 2024
    2024
    Citations: 4
  • Enhancing Pali Manuscript Interpretation with Artificial Neural Network Techniques
    S Gudadhe, A Bardekar, A Ranit
    International Conference on Data Engineering and Communication Technology, 69-82 , 2024
    2024
  • Investigation of Mechanical Behavior of Steel Fiber-Reinforced Geopolymer Concrete Under Multi-Axial Stress Conditions
    SM Ranit, A.B. , Futane, N.S. , Dhawale, V.R. , Ingalkar, R.S. , Harle
    Advances in Transdisciplinary Engineering , 2024
    2024
  • NEURAL NETWORK-DRIVEN FORECASTING OF AFTERSHOCK DYNAMICS FOR ENHANCED SEISMIC RESILIENCE IN STRUCTURAL ENGINEERING
    S. M. Harle,A. B. Ranit, P.S.Chaoudhari
    ISET Journal of Earthquake Technology 61 (02), 55-71 , 2024
    2024
  • INTEGRATING MACHINE LEARNING AND NLP EFFICIENT RETRIEVAL OF CHARACTERS IN PALI SCRIPT PRESERVATION
    SR Gudadhe, AA Bardekar, AB Ranit
    Juni Khyat t (जूनी ख्यात) 14 (01) , 2024
    2024
    Citations: 2
  • Investigation of Mechanical Behavior of Steel Fiber-Reinforced Geopolymer Concrete Under Multi-Axial Stress Conditions
    AB Ranit, NS Futane, VR Dhawale, SM Dhawade, RS Ingalkar, SM Harle
    Hydraulic and Civil Engineering Technology IX: Proceedings of the 9th … , 2024
    2024
  • AI Development for Translating Indian Historical Devanagari Scripts into the Pali Language : A Technical Approach
    ABR Sangita R. Gudadhe, Aashish A. Bardekar
    ALOCHANA JOURNAL 13 (10), 253-256 , 2024
    2024
  • Structural Performance of LGS and Ferrocement Composite Element
    A Akarte, A Gathe, S Harle, AB Ranit, MV Mohod, SS Nibhorkar
    Structural Engineering Convention, 523-530 , 2023
    2023

MOST CITED SCHOLAR PUBLICATIONS

  • Identifying factors affecting construction labour productivity in Amravati
    A Sangole, A Ranit
    International Journal of Science and Research 4 (5), 1585-1588 , 2015
    2015
    Citations: 34
  • Different techniques of flood forecasting and their applications
    AB Ranit, PV Durge
    2018 International Conference on Research in Intelligent and Computing in … , 2018
    2018
    Citations: 19
  • Project management using primavera P6
    A Mahure, A Ranit
    Int. J. Eng. Res. Technol 241, 244 , 2018
    2018
    Citations: 16
  • Flood forecasting by using machine learning
    AB Ranit, PV Durge
    2019 International Conference on Communication and Electronics Systems … , 2019
    2019
    Citations: 8
  • Machine learning and optimization in hybrid energy storage systems: Integrating MPC, PSO, MILP, and ANN for grid stability and efficiency
    JL Rajesh M. Bhagat, Dilendra B. Jasutkar, Amitkumar B. Ranit, Vikrant S ...
    International Journal of Electrical Power & Energy Systems 170, 1-16 , 2025
    2025
    Citations: 7
  • AI-driven sustainable concrete mix design: Hybrid deep Q-Learning and genetic algorithms-based multi-objective machine learning optimizations for high structural strength, low …
    EESM Amruta A. Yadav a , Sneha G. Hirekhan a , Pranita S. Bhandari b ...
    Structures 82 , 2025
    2025
    Citations: 5
  • A novel approach using machine learning and NLP for revolutionizing Pali manuscript conservation
    SR Gudadhe, AA Bardekar, AB Ranit
    2024 4th International Conference on Sustainable Expert Systems (ICSES), 844-848 , 2024
    2024
    Citations: 4
  • Neural networks, cnns, and hybrid models in structural retrofitting: a deep learning perspective
    PKS Bhadauria, N Zanjad, SG Kalamkar, A Ranit, P Chaudhary
    Asian Journal of Civil Engineering 26 (11), 4499-4516 , 2025
    2025
    Citations: 2
  • Tailoring the pore structure of mesoporous composite agro‑based adsorbents for the enhanced removal of Cu(II) and Ni(II) heavy metal ions from wastewater
    RM Bhagat, SR Khandeshwar, AB Ranit, MP Bhorkar, BP Nandurkar, ...
    Clean Technologies and Environmental Policy , 2025
    2025
    Citations: 2
  • INTEGRATING MACHINE LEARNING AND NLP EFFICIENT RETRIEVAL OF CHARACTERS IN PALI SCRIPT PRESERVATION
    SR Gudadhe, AA Bardekar, AB Ranit
    Juni Khyat t (जूनी ख्यात) 14 (01) , 2024
    2024
    Citations: 2
  • A Review Paper on Construction Waste Management and its Impact on Cost of The Project
    P Baitule, NS Futane, AB Ranit
    SSRG International Journal of Civil Engineering 7 (7), 20-22 , 2020
    2020
    Citations: 2
  • Review of Bayesian Approaches for Structural Integrity Assessment and Damage Identification
    P Bhadauria, AB Ranit, PS Chaudhary, KA Dongre, SM Harle, AP Bhagat
    Operations Research Forum 7 (1), 8 , 2026
    2026
    Citations: 1
  • Innovative approaches to fire-resistant building materials: a review
    PKS Bhadauria, AB Ranit, PS Chaudhary, KA Dongre, SM Harle, ...
    Life Cycle Reliability and Safety Engineering, 1-14 , 2025
    2025
    Citations: 1
  • Techniques of Flood Forecasting and Their Applications
    PVD Amitkumar Ranit
    International Conference on Intelligent Data Communication Technologies and … , 2019
    2019
    Citations: 1
  • Identifying the Factors which affects the Labour Productivity and Improving the Labour Productivity in Construction Using Statistical Tests
    R Sibiya
    International Journal for Modern Trends in Science and Technology 5 (11), 34-39 , 2019
    2019
    Citations: 1
  • Evaluation of Quality Management in Irrigation Projects
    AV Guldekar, AB Ranit
    International Journal of Science and Research (IJSR) , 2016
    2016
    Citations: 1
  • Reducing Carbon Footprint in the Construction Industry: Strategies from Design to Operation
    SM Harle, AB Ranit, S Ambadkar, S Bejalwar
    Reduction of Industrial Carbon Footprint, 43-91 , 2026
    2026
  • Neural networks, CNNs, and hybrid models in structural retrofitting: a deep learning perspective
    ARPC Pradeep K. S. Bhadauria, Nilesh Zanjad, Sanket Gajanan Kalamkar
    Asian Journal of Civil Engineering Building and Housing , 2025
    2025
  • GREEN BUILDING PROJECT MANAGEMENT APPROACH IN CONSTRUCTION PHASES
    DABR Aachal Bhaurao Kore
    DASTAVEJ RESEARCH JOURNAL 55 (1), 12-17 , 2025
    2025
  • Impact of Shear Wall Placement on Seismic Performance of Vertically Irregular Structures
    SGT Shrikant M. Harle, Amitkumar B. Ranit, Pravin Shankarrao Choudhary ...
    Jordan Journal of Civil Engineering 19 (2), 211-229 , 2025
    2025

Publications

Scopus ID= 57204806968,