FAULT DIAGNOSIS WITH COMPUTATIONAL INTELLIGENCE: PART 1

“fired,” i.e., its Then part is made true, generating new facts and data which in turn cause other rules to “fire.” Reasoning stops when no more new rules can fire. In backward chaining or goal-driven inferencing, a goal to be proved is specified. If the goal cannot be immediately satisfi[r]

7.1 Introduction
Design is a process of generating a description of a set of methods that satisfy all requirements. Generally speaking, a design process model consists of the following four major activities: analysis of a problem, conceptual design, embodiment design, and detailing design. Am[r]

The necessary and sufficient condition for a machine tool to be parallel is I 1. However, for a parallel machine to perform machining in sequential operations, we can simply set i 1 and l 1.
A mixed integer programming model will be introduced in Section 8.2 to model t[r]

50 trials is 1635.7. The worst plan among the 50 solutions has a cost of 1786. The GA found the best plans (cost = 1598) 27 times out of 50 trials (54%). One of the best plans found is shown in Table 9.5 . Compared with the best plans found for setting 1, this plan employs more machi[r]

6 0.0103 0.0103 0.0103 0.0572 0.1992 0.2349 1 0.2184 0.212 0.0364 0.0146 0.0146 0.0146 0.0087
13 0.0103 0.0103 0.0103 0.0572 0.1951 0.2184 0.2184 1 0.2253 0.0602 0.0384 0.0384 0.0384 0.0325
11 0.0057 0.0057 0.0057 0.0526 0.1901 0.212 0.212 0.2253 1 0.0581 0.0364 0.0364 0.036[r]

First, design features are identified to cover design attributes of all the parts. Features are design primitives or low-level designs, along with their attributes, qualifiers and restrictions which affect func- tionality or manufacturability. Features can be described by form (size and shape[r]

5.3 Justification of Representing Objectives with Fuzzy Sets
Unlike ordinary sets, fuzzy sets have gradual transitions from membership to nonmembership, and can represent both very vague or fuzzy objectives as well as very precise objectives [Yager 1978]. For example, when considering net[r]

Consider an MAS that evolves, transitioning from an initial state through a chain of intermediate states until it reaches its goal in a final state. A main driving force for MAS dynamics during this transition is information exchange among agents. While the MAS evolves through its states toward th[r]

Faculty of Computer Science and Information System, Universiti Teknologi Malaysia
Abstract
I n this chapter, we propose a new method based on genetic algorithms (GAs) for fuzzy artificial neural network (FANN) learning to improve its accuracy in measuring customer service satis[r]

used to solve 20 problems with size ranging from 50 250 to 70 1400 (machines parts) and evaluated
by the measure clustering effectiveness defined by the authors. The results showed that the approach had a better performance for smaller size problems.
Lee and Fisher [32] took both design[r]

where
Equation (15.14)
f ( t ) and F ( w ) are called a pair of Fourier transforms. Equation 15.13 implies that f ( t ) signal can be decomposed into a family in which harmonics e iwt and the weighting coefficient F ( w ) represent the amplitudes of the harmonics in f ( t ). F ( w ) is i[r]

In this thesis work one of the evolutionary algorithms package, the evolutionary strategy package has been modified and then applied to a real world bioinformatics problem: to search the[r]

10.4.2.7 Machine-Based Representation
A chromosome is encoded as a sequence of machines and a schedule is constructed with shifting bottleneck heuristic based on the sequence [Dorndorf and Pesch, 1995]. The shifting bottleneck heuristic sequences the machines one by one, successively, eac[r]

Three diverse neural network predictive process models were presented using real-world engineering problems. The ceramic slip casting application was part of a larger project for which only the neural network development was discussed in this chapter. The final product of this project has bee[r]

In this chapter the characteristics of the manufacturing processes were analyzed. According to this, the monitoring and control problems were identified and the use of artificial neural networks to solve them was justified. Types of sensor signals, network structures, and output variables for monito[r]

The NIST ISD have been working with the material handling industry, specifically on automated guided vehicles (AGVs), to develop next generation vehicles. A few example accomplishments in this area include: determining the high impact areas according to the AGV industry, partnering with