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Jayaprakash Vemuri

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Associate Professor

Mahindra University

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Research Interests

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Professors in Structural Engineering

Recent Grants

Grant: Close

Experimental Investigation of Structural Response under Near Fault Ground Motions using Shake Table Studies

Open Date: 2022-01-01

Close Date: 2024-01-01

Grant: Close

Development of High Performance Multifunctional Geopolymer Composites

Open Date: 2018-01-01

Close Date: 2020-01-01

Articles (20)

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Collaborators (1)

Sri Kalyana Rama Jyosyula

Assistant Professor

Mahindra University

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Jayaprakash Vemuri

Research Interests

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Recent Grants

Articles (20)

Directional displacement demand in tall RC buildings under pulse-like ground motions

Machine learning based prediction of vertical ground motion duration using hyperparameter optimization

A comparative study of ground motion parameters at bedrock and surface level in Kathmandu Basin

Effect of Soil Structure Interaction on the Response of a Lumped Mass Model

Evaluation of intrinsic mode function for the identification of pulse-like ground motion using machine learning technique

Exploring the association of ground motion intensity measures and demand parameters with ANN-based predictive modeling and uncertainty analysis

Prediction Of Maternal Health Risk Factors Using Machine Learning Algorithms

The Role of Machine Learning in Obesity Prediction Across Latin American Populations: A Study on the Effectiveness of Different Approaches

Time–Frequency Analysis of Strong Ground Motions from the 1994 Northridge Earthquake

A Novel Implementation of Tableau Software for the Visualisation of Seismic Data from Himalayan Region

Evaluation of Machine Learning Algorithms for Predicting Compressive Strength of Geopolymer Concrete at High Temperatures

Evaluation of constant ductility displacement response spectra for near-fault ground motions of the 1999 Chi-Chi earthquake, Taiwan

Forecasting duration characteristics of near fault pulse-like ground motions using machine learning algorithms

Prediction of Effective Duration of Vertical Ground Motions Based on Machine Learning Algorithms

Prediction of storey drift for reinforced concrete structures subjected to pulse-like ground motions using machine learning classification models

Predictive Modeling for Compressive Strength in Sustainable Concrete Using Machine Learning Techniques

Reservoir outflow prediction using adaptive neuro-fuzzy interference system

Shapelet-informed machine learning classifiers: A path towards precise identification of pulse-like ground motions

Simulation of pulse-like ground motions with directionality effect for the 2001 M<sub>w</sub> 7.6 Bhuj, India earthquake and sensitivity analysis of uncertain model input parameters

Strong ground motion characteristics observed in the February 6, 2023 M<sub>W</sub>7.7 Türkiye earthquake

Collaborators (1)

Sri Kalyana Rama Jyosyula

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