Development of an Industrial Application with Neuro-Fuzzy Systems

In this paper, our objective is dedicated to the detection of a deterioration in the estimated operating time by giving preventive action before a failure, and the classification of breakdowns after failure by giving the action of the diagnosis and / or maintenance. For this reason, we propose a new Neuro-fuzzy assistance prognosis system based on pattern recognition called "NFPROG" (Neuro Fuzzy Prognosis). NFPROG is an interactive simulation software, developed within the Laboratory of Automation and Production (LAP) -University of Batna, Algeria. It is a four-layer fuzzy preceptor whose architecture is based on Elman neural networks. This system is applied to the cement manufacturing process (cooking process) to the cement manufacturing company of Ain-Touta-Batna, Algeria. And since this company has an installation and configuration S7-400 of Siemens PLC PCS7was chosen as a programming language platform for our system.

A Fuzzy Logic Approach for Image Restoration and Content Preserving

Image filtering, which removes or reduces noises from the contaminated images, is an important task in image processing. This paper presents a novel approach to the problem of noise reduction for gray-scale images. The proposed technique is able to remove the noise component, while adapting itself to the local noise intensity. In this way, the proposed algorithm can be considered as a modification of the median filter driven by fuzzy membership functions. Experimental results are compared to static median filter by numerical measures and visual inspection. As was expected, the new filter shows better performances.

Automation and Fuzzy Control of a Manufacturing System

The automation of manufacturing systems is a major obligation to the developments because of exponential industrial equipment, and programming tools, so that growth needs and customer requirements. This automation is achieved in our work through the application programming tools from Siemens, which are PCS 7 (Process Control System) for industrial process control and FuzzyControl++ for fuzzy control. An industrial application is designed, developed and implemented in the cement factory in Ain-Touta (S.CIM.AT) located in the province of Batna, East of Algeria. Especially in the cement mill which gives the final product that is the cement.

More on Fuzzy Topological Spaces on Fuzzy Space

The fuzzy topological space was introduced by Dip in 1999 depending on the notion of fuzzy spaces. Dip’s approach helps to rectify the deviation in some definitions of fuzzy subsets in fuzzy topological spaces. In this paper, further definitions, and theorems on fuzzy topological space fill the lack in Dip’s article. Different types of fuzzy topological space on fuzzy space are presented such as co-finite, co-countable, right and left ray, and usual fuzzy topology. Furthermore, boundary, exterior, and isolated points of fuzzy sets are investigated and illustrated based on fuzzy spaces. Finally, separation axioms are studied on fuzzy spaces

Logarithmic Divergence Measure for Fuzzy Matrix and Application

This paper introduces a new divergence measure for a fuzzy matrix with proof of its validity. In addition, the properties are proved for the new fuzzy divergence measure. A method to solve decision making problem is developed by using the proposed fuzzy divergence measure. Finally, the application of this fuzzy divergence measure to decision making is shown using real-life example

Prime Fuzzy Bi-Ideals in Near-Subtraction Semigroups

A study on fuzzy prime ideals in near-subtraction semigroups is already known. We have to expand the concept of prime fuzzy bi-ideals in near-subtraction semigroups and analyse some of its properties to characterize it. This will lead to learn a new type of fuzzy ideal and to develope the researcher to made their research.

Proposed Fuzzy Logic Controller for Buck DC-DC Converter

This paper provides the design for buck DC-DC converter system using fuzzy logic as well as sliding mode method. Design of fuzzy logic controller will be based on improvement of imperfection of the sliding mode controller, in particular the robustness and response time of the system. The simulation results of both systems using fuzzy logic and sliding mode are shown as well as compared to signify better of the two.

Detection of Glaucoma in Retinal Fundus Images using Fast Fuzzy C Mean Clustering

Glaucoma is one of the major causes of vision loss in today’s world. Glaucoma is a disease in the eye where fluid pressure in the eye increases; if it is not timely cured, the patient may lose their vision. Glaucoma can be detected by examining boundary of optics cup and optics disc acquired from fundus images. The proposed method suggest automatic detect the boundary of optics cup and optics disc with processing of fundus images. This paper explores the new approach fast fuzzy C-mean technique for segmenting the optic disc and optic cup in fundus images. Results evaluated by fast fuzzy C mean a technique is faster than fuzzy C-mean method. The proposed method reported results to 91.91%, 90.49% and 90.17% when tested on DRIONS, DRIVE and STARE on publicly available databases of fundus images.

Meteorological Risk Assessment for Ships with Fuzzy Logic Designer

Fuzzy Logic, an advanced method to support decision-making, is used by various scientists in many disciplines. Fuzzy programming is a product of fuzzy logic, fuzzy rules, and implication. In marine science, fuzzy programming for ships is dramatically increasing together with autonomous ship studies. In this paper, a program to support the decision-making process for ship navigation has been designed. The program is produced in fuzzy logic and rules, by taking the marine accidents and expert opinions into account. After the program was designed, the program was tested by 46 ship accidents reported by the Transportation Safety Investigation Center of Turkey. Wind speed, sea condition, visibility, day/night ratio have been used as input data. They have been converted into a risk factor within the Fuzzy Logic Designer application and fuzzy rules set by marine experts. Finally, the expert's meteorological risk factor for each accident is compared with the program's risk factor, and the error rate was calculated. The main objective of this study is to improve the navigational safety of ships, by using the advance decision support model. According to the study result, fuzzy programming is a robust model that supports safe navigation.

Fuzzy Variable Frame analysis for Speech Recognition

Recent works in machine learning has focused on models such as Support Vector Machine(SVM), Artificial Neural Network(ANN) and Long Short Term Memory (LSTM), for automatically controlling the generalization and parameterization of the optimization process. This paper presents a fuzzy interpretation frame analysis procedure using LSTM classifier for noisy speech at word level using thresholding and local maxima procedure at framing level for the recognition process. Front end MFCC procedure has been modified in the framing phase to reduce the number of noisy frames using thresholding at two level local maxima procedures. A comparative results of various classifiers like SVM with kernel function, ANN and LSTM are tabulated for recognition accuracies. A fuzzy interpretation at the framing level to calculate optimal frames has been presented in this paper. In the proposed work 20% of unwanted processing of frames is reduced that equally produces the accuracies obtained by fixed frame analysis. An investigation shows that the obtained features with LSTM decrease word error rate still by 1% as increasing the recognition accuracy from 98 to 99% . approach.