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Full-Text Articles in Electrical and Computer Engineering
Dayalbagh Educational Institute Soft Computing Edge Cutting Technology Lab (Deisel), D. K. Chaturvedi
Dayalbagh Educational Institute Soft Computing Edge Cutting Technology Lab (Deisel), D. K. Chaturvedi
D. K. Chaturvedi Dr.
Dayalbagh Educational Institute Soft Computing Edge Cutting Technology Lab (DEISEL) Group consiting of a Professor Incharge, four Teaching Staff members, five Non-Teaching Staff members, five Ph.D. Students, six M. Tech. Students. The objective of DEISEL is to to exploit the tolerance for imprecision uncertainty, approximate reasoning and partial truth to achieve tractability, robustness, low solution cost, and close resemblance with human like decision making to find an approximate solution to an imprecisely/precisely formulated problem. The challenge is to exploit the tolerance for imprecision by devising methods of computation which lead to an acceptable solution at low cost. This, in essence, …
Programs Of Fuzy Systems, D. K. Chaturvedi
Programs Of Fuzy Systems, D. K. Chaturvedi
D. K. Chaturvedi Dr.
The zip file contains c programs of fuzzy system.
Matlab Program Of Genetic Algorithms, D. K. Chaturvedi
Matlab Program Of Genetic Algorithms, D. K. Chaturvedi
D. K. Chaturvedi Dr.
The zip file contains Matlab program of genetic algorithms and their varients.
Ann /Gn Programs, D. K. Chaturvedi
Ann /Gn Programs, D. K. Chaturvedi
D. K. Chaturvedi Dr.
The file contains programms of multi layer feedforward backpropagation ANN, GN and their varients.
Load Forecasting Using Genetic Algorithms, D. K. Chaturvedi, R. K. Mishra, A. Agarwal
Load Forecasting Using Genetic Algorithms, D. K. Chaturvedi, R. K. Mishra, A. Agarwal
D. K. Chaturvedi Dr.
Genetic Algorithms (GAs) are gaining popularity in many engineering and scientific applications due to their enormous advantages such as adaptibility, ability to handle non-linear, ill defined and probabilistic problems. In this paper load forecasting problem on long term basis is formulated in the frame work of Genetic Algorithms. The results of GAs are compared with the central Electricity Authority (CEA) forecasted data to demonstrate the effectiveness of the proposed algorithms.