S. S. Tambe

发表

Consider genetic programming for process identification

Bhaskar D. Kulkarni, S. S. Tambe, R. K. Dahule, 1999 .

STUDY OF A LABORATORY-SCALE FROTH FLOTATION PROCESS USING ARTIFICIAL NEURAL NETWORKS

S. S. Tambe, B. D. Kulkarni, V. K. Kalyani, 2007 .

Stochastic approach to the analysis of chemically reactive systems

S. S. Tambe, 1985 .

Prediction of °API Values of Crude Oils by Use of Saturates/Aromatics/Resins/Asphaltenes Analysis: Computational-Intelligence-Based Models

Purva Goel, S. S. Tambe, Kumar Saurabh, 2017 .

Biodegradable iron chelate for H2S abatement: Modeling and optimization using artificial intelligence strategies

Bhaskar D. Kulkarni, S. S. Tambe, Y. P. Badhe, 2014 .

An artificial intelligence tool for bioprocess monitoring: application to continuous production of gluconic acid by immobilized Aspergillus niger

S. S. Tambe, N. V. Sankpal, J.J.S. Cheema, 2001, Biotechnology Letters.

Applications of Support Vector Machines as a Robust tool in High Throughput Virtual Screening

Renu Vyas, Bhaskar D. Kulkarni, S. S. Tambe, 2012 .

Consider genetic algorithms to optimize batch distillation

Bhaskar D. Kulkarni, S. S. Tambe, R. K. Dahule, 2001 .

Prediction of Higher Heating Value of Solid Biomass Fuels Using Artificial Intelligence Formalisms

S. S. Tambe, S. Tambe, S. B. Ghugare, 2013, BioEnergy Research.

Optimization of Continuous Distillation Columns Using Stochastic Optimization Approaches

S. S. Tambe, R. K. Dahule, Bhaskar D. Kulkarni, 2001 .

Kinetics of Isopropylation of Benzene over HBeta Catalyst

S. S. Tambe, S. Tambe, N. Pradhan, 2001 .