An Efficient Soft Computing Approach for Solving the Two-Stage Transportation Problem with Fixed Costs

2019 ◽  
pp. 523-532 ◽  
Author(s):  
Ovidiu Cosma ◽  
Petrica Pop ◽  
Ioana Zelina
Keyword(s):  
Soft Computing ◽  
Transportation Problem ◽  
Fixed Costs ◽  
Two Stage ◽  
Computing Approach

A novel matheuristic approach for a two-stage transportation problem with fixed costs associated to the routes

2020 ◽  
Vol 118 ◽  
pp. 104906 ◽  
Author(s):  
Ovidiu Cosma ◽  
Petrică C. Pop ◽  
Daniela Dănciulescu
Keyword(s):  
Transportation Problem ◽  
Fixed Costs ◽  
Two Stage

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

Review of Fault Diagnosis System using Soft Computing Approach

2020 ◽  
Author(s):  
Nitin N. Mandaogade ◽  
Prashant V. Ingole
Keyword(s):  
Fault Diagnosis ◽  
Soft Computing ◽  
Diagnosis System ◽  
Fault Diagnosis System ◽  
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.

Modeling and Analysis of Surface Roughness with Statistical and Soft Computing Approach

2021 ◽  
Vol 106 ◽  
pp. 109-115
Author(s):  
L.B. Abhang ◽  
M. Hameedullah
Keyword(s):  
Surface Roughness ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Prediction Models ◽  
Tool Geometry ◽  
Modeling And Analysis ◽  
Empirical Prediction ◽  
Lathe Machine ◽  
Carbide Inserts ◽  
Computing Approach

The objective of this study focuses on developing empirical prediction models using response regression analysis and fuzzy-logic. These models latter can be used to predict surface roughness according to technological variables. The values of surface roughness produced by these models are compared with experimental results. Experimental investigation has been carried out by using scientific composite factorial design on precision lathe machine with tungsten carbide inserts. Surface roughness measured at end of each experimental trial (three times), to get the effect of machining conditions and tool geometry on the surface finish values. Research showed that soft computing fuzzy logic model developed produces smaller error and has satisfactory results as compared to response regression model during machining.

A soft computing approach for learning to aggregate rankings

2016 ◽  
Author(s):  
Javier Alvaro Vargas Muñoz
Keyword(s):  
Soft Computing ◽  
Computing Approach
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