• Publications
  • Influence
Mapping the input–output relationship in HSLA steels through expert neural network
Modification of the architecture of the artificial neural network is done to accommodate the information available from the knowledge base in the field of materials science for thermomechanicallyExpand
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Soft computing techniques in advancement of structural metals
Abstract Current trends in the progress of technology demand availability of materials resources ahead of the advancing fronts of the application areas. During the last couple of decades, significantExpand
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Techniques to isolate dolphin whistles and other tonal sounds from background noise
TLDR
Automatic identification of groups of dolphins has become desirable for comparison of behaviour involving a population of wild dolphins. Expand
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Designing High Strength Multi-phase Steel for Improved Strength-Ductility Balance Using Neural Networks and Multi-objective Genetic Algorithms
The properties of steels depend in a complex way on their composition and heat treatment and neural networks have therefore recently been widely used for capturing these relationships. Two differentExpand
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Analyses of anti-wear and extreme pressure properties of castor oil with zinc oxide nano friction modifiers
Abstract The present work investigated the tribological properties of zinc oxide nano friction modifiers (FM) based castor oil in different concentrations between steel surfaces. The nano lubricantsExpand
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Segmentation of dual phase steel micrograph: An automated approach
Abstract Digital image processing is used to analyze the microscopic images of the materials. Extraction of grains/phases present in the material is the fundamental step to achieve the description ofExpand
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Adsorption-desorption of Boron in Major Soils of India
Studies on adsorption of boron (B) undertaken in 12 soils representing different agro-ecological regions of India revealed that the adsorption of added B was in the order: Vertisols > Inceptisols >Expand
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Optimization of mechanical property and shape recovery behavior of Ti-(∼49 at.%) Ni alloy using artificial neural network and genetic algorithm
Abstract Multi-objective genetic algorithm based searching is used for designing the process schedule of Ti-(∼49 at.%) Ni alloy, to achieve optimum mechanical property and shape recovery behavior.Expand
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Genetic algorithm based optimization for multi-physical properties of HSLA steel through hybridization of neural network and desirability function
A genetic algorithm (GA) based optimization of the composite desirability of the tensile properties of thermomechanically processed high strength low alloy (HSLA) steel plates is proposed. TheExpand
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