Rajesh Singh
University of Lucknow
37 Papers
75 Citations
Rajesh Singh is an academic researcher from University of Lucknow. The author has contributed to research in topics: Slope stability analysis & Slope stability. The author has an hindex of 18, co-authored 37 publications. Previous affiliations of Rajesh Singh include Indian Institute of Technology Bombay.
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Papers
Estimation of elastic constant of rocks using an ANFIS approach
Rajesh Singh,Ashutosh Kainthola,Trilok Singh +2 more
- 01 Jan 2012
TL;DR: The neuro fuzzy system is applied to predict the rock Young's modulus to overcome the limitation of ANN and fuzzy logic and endow with high performance of predictive neuro-fuzzy system to make use for prediction of complex rock parameter.
378
Effect of Varied Durations of Thermal Treatment on the Tensile Strength of Red Sandstone
N. N. Sirdesai,N. N. Sirdesai,N. N. Sirdesai,Trilok Singh,Pathegama Gamage Ranjith,Rajesh Singh +5 more
TL;DR: In this paper, Singh et al. studied the effect of temperature on the tensile strength of rocks in coal gasification and found that exposure to high temperatures for an extended duration results in the formation of thermal stresses, thereby initiating expansion as well as accelerating the failure process.
144
A comparative study of generalized regression neural network approach and adaptive neuro-fuzzy inference systems for prediction of unconfined compressive strength of rocks
TL;DR: In this article, generalized regression neural network (GRNN) and adaptive neuro-fuzzy inference systems (ANFIS) were used to predict unconfined compressive strength from seismic wave velocities (Compressional wave, Shear wave) and density of rock.
130
Stability evaluation of road-cut slopes in the Lesser Himalaya of Uttarakhand, India: conventional and numerical approaches
TL;DR: In this article, a slope stability analysis was performed of road-cut slopes along about 20 km of NH-109 from Rudraprayag to Agastmuni in the state of Uttarakhand in India.
129
Prediction of geomechanical parameters using soft computing and multiple regression approach
TL;DR: The present study focused on the determination of parameters like uniaxial compressive strength, tensile strength, point load index and Young’s modulus from very easily determinable physical parameters viz. density, porosity, and compressional wave velocity using multiple variable regression analysis and adaptive neuro-fuzzy inference system.
108