A5012785534- Hydrological Forecasting Using AI
- Flood Risk Assessment and Management
- Hydrology and Watershed Management Studies
- Ocean Waves and Remote Sensing
- Energy Load and Power Forecasting
- Infrastructure Maintenance and Monitoring
- Concrete Corrosion and Durability
- Tropical and Extratropical Cyclones Research
- Smart Materials for Construction
- Stock Market Forecasting Methods
- Geotechnical Engineering and Underground Structures
- Reservoir Engineering and Simulation Methods
- Hydrology and Drought Analysis
- Vibration and Dynamic Analysis
- Mechanical stress and fatigue analysis
- Metaheuristic Optimization Algorithms Research
- Civil and Geotechnical Engineering Research
- Climate variability and models
- Soil Moisture and Remote Sensing
- Neural Networks and Applications
- Fault Detection and Control Systems
- Recycled Aggregate Concrete Performance
- Non-Destructive Testing Techniques
- Water resources management and optimization
- Structural Load-Bearing Analysis
International Institute of Information Technology
2015-2023
Savitribai Phule Pune University
2014-2018
Precipitation is a major factor controlling the hydrology of region. It has been experienced that precipitation data are sometimes lost by virtue instrument malfunctioning, human error(s), climatic conditions which becomes an impediment in hydrologic and hydraulic designs where rainfall series input. Such missing values could be retrieved using estimated value employing large number conventional hard computing techniques such as normal ratio method, inverse distance method to name few. The...
This article presents comparison of Artificial Neural Networks (ANNs) and Hydrologic Engineering Centre-Hydrologic Modelling System (HEC-HMS) model for rainfall-runoff (R-R) process. Aim the present work is to forecast runoff one day ahead at Shivade station Upper Krishna Basin, India, using 17 years daily rainfall discharge data. The R-R modelling can be exercised various traditional methods which generally require exogenous data in form basin parameters. Unavailability such becomes major...
Carbonation is one of the critical durability issues in reinforced concrete structures terms their structural integrity and safety may cause fatal deterioration corrosion steel reinforcement if ignored. Many researchers have performed a considerable number studies to predict carbonation structures. However, it still challenging depth or coefficient, as they depend on various factors. Therefore, creating model that can learn from available data using Data Driven Techniques (DDT) step forward...
In the present work a hybrid Neuro-Wavelet Technique is used for forecasting waves up to 6 hr, 12 18 hr and 24 in advance using hourly measured significant wave heights at an NDBC station 41004 near east coast of USA. The NW employed by combining two methods, Discrete Wavelet Transform Artificial Neural Networks. data previously spanning over 2 years from 2010 2011 calibrate test models. discrete wavelet transform NWT analyzes frequency signal with respect time different scales. It...
In the current study 28 day strength of Recycled Aggregate Concrete (RAC) and Fly ash (class F) based concrete is predicted using Artificial Neural Network (ANN), Multigene Genetic Programming (MGGP) Model Tree (MT). Four sets models were designed for per cubic proportions materials, Properties materials non-dimensional parameters as input parameters. The shows that in good agreement with observed data also generalize well to untrained data. ANN outperforms MGGP MT terms model performance....
Shark Tank-India: A television show in which start-ups from various fields like food to machinery etc. pitch their idea a panel of investors (sharks) hopes striking deal the form equity or royalties for money. 85 episodes Tank - India divided into two seasons aired 2021 and 2023. The whole process pitching final can be phases: Phase I is done II amount deal. work presented here an attempt predict if after pitching, will II, using Machine Learning Techniques such as Artificial Neural...
In recent days numerical models like Wavewatch are used for grid based wave forecast all over the world Considering resolution it is difficult to scale down a location specific forecast. As result univariate forecasting may be employed where in previous values of waves up few hours advance. However such suffer vital issue 'removal phase lag' which has been recognized by many researchers and attributed high autocorrelation between last two observed time series modelling. Authors have...
Abstract Estimation and prediction of the real time information oceanographic parameters is vital importance in India as more than 25% population resides along coastlines. Information significant wave heights necessary to deal with many activities almost all ocean engineering applications depends on it. Presently Indian National Centre for Ocean Services (INCOIS) provides forecasts regional local level ranging from 3 hours 7 days ahead using numerical models ( www.incois.res.in ). It evident...