A soft computing approach to projecting locational marginal price

2012 ◽  
Vol 22 (6) ◽  
pp. 1115-1124 ◽  
Author(s):  
Nnamdi I. Nwulu ◽  
Murat Fahrioglu
Keyword(s):  
Soft Computing ◽  
Locational Marginal Price ◽  
Marginal Price ◽  
Computing Approach

SOFT COMPUTING APPROACH TO DETECT FAULT IN INDUCTION MOTOR

2018 ◽  
Vol 12 (2) ◽  
pp. 6
Author(s):  
SEKHAR PUHAN PRATAP ◽  
BEHERA SUDARSAN ◽  
◽  
Keyword(s):  
Induction Motor ◽  
Soft Computing ◽  
Computing Approach

Towards A Soft Computing Approach to Document Clustering

2017 ◽  
Author(s):  
Muhammad Rafi ◽  
Sufyan Shahid ◽  
Junaid Aftab ◽  
Muhammad Faizan Uddin ◽  
Muhammad Shahid Shaikh
Keyword(s):  
Soft Computing ◽  
Document Clustering ◽  
Computing Approach

scholarly journals A Soft Computing Approach to Crack Detection and Impact Source Identification with Field-Programmable Gate Array Implementation

2013 ◽  
Vol 2013 ◽  
pp. 1-12 ◽  
Author(s):  
Arati M. Dixit ◽  
Harpreet Singh
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Fuzzy Inference System ◽  
Source Identification ◽  
Field Programmable Gate Array ◽  
Crack Detection ◽  
Fuzzy Inference ◽  
Inference System ◽  
Field Programmable ◽  
Computing Approach

The real-time nondestructive testing (NDT) for crack detection and impact source identification (CDISI) has attracted the researchers from diverse areas. This is apparent from the current work in the literature. CDISI has usually been performed by visual assessment of waveforms generated by a standard data acquisition system. In this paper we suggest an automation of CDISI for metal armor plates using a soft computing approach by developing a fuzzy inference system to effectively deal with this problem. It is also advantageous to develop a chip that can contribute towards real time CDISI. The objective of this paper is to report on efforts to develop an automated CDISI procedure and to formulate a technique such that the proposed method can be easily implemented on a chip. The CDISI fuzzy inference system is developed using MATLAB’s fuzzy logic toolbox. A VLSI circuit for CDISI is developed on basis of fuzzy logic model using Verilog, a hardware description language (HDL). The Xilinx ISE WebPACK9.1i is used for design, synthesis, implementation, and verification. The CDISI field-programmable gate array (FPGA) implementation is done using Xilinx’s Spartan 3 FPGA. SynaptiCAD’s Verilog Simulators—VeriLogger PRO and ModelSim—are used as the software simulation and debug environment.

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