scholarly journals SOFT COMPUTING SYSTEM FOR THE DIAGNOSIS OF HORMONAL IMBALANCE

2020 ◽  
Vol 7 (6) ◽  
pp. 30-42
Author(s):  
Victor Ekong
Keyword(s):  
Genetic Algorithm ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Medical Condition ◽  
Real Life ◽  
Computing System ◽  
Human Existence ◽  
Life Problems ◽  
Hormonal Imbalance ◽  
Soft Computing Techniques

Soft computing, as a science of modelling systems, applies techniques such as evolutionary computing, fuzzy logic, and their hybrids to solve real life problems. Soft computing techniques are quite tolerant to incomplete, imprecise, and uncertainty when dealing with complex situations. This study adopts a hybrid of genetic algorithm and fuzzy logic in diagnosing hormonal imbalance. Hormones are chemical messengers that are vital for growth, reproduction, and are essential for human existence. Hormones may sometimes not be balanced which is a medical condition that often go unnoticed and it’s quite difficult to be diagnosed by medical experts. Hormonal imbalance has several symptoms that could also be confused for other ailments. This proposed system serves as support for medical experts to improve the precision of diagnosis of hormonal imbalance. The study further demonstrates the effective hybridization of genetic algorithm and fuzzy logic in resolving human problems.

Soft case-based reasoning

2005 ◽  
Vol 20 (3) ◽  
pp. 267-269 ◽  
Author(s):  
WILLIAM CHEETHAM ◽  
SIMON SHIU ◽  
ROSINA O. WEBER
Keyword(s):  
Neural Network ◽  
Fuzzy Logic ◽  
Soft Computing ◽  
Network Theory ◽  
Probabilistic Reasoning ◽  
Case Based Reasoning ◽  
Case Representation ◽  
Soft Computing Techniques ◽  
Neural Network Theory ◽  
Case Based

The aim of this commentary is to discuss the contribution of soft computing—a consortium of fuzzy logic, neural network theory, evolutionary computing, and probabilistic reasoning—to the development of case-based reasoning (CBR) systems. We will describe how soft computing has been used in case representation, retrieval, adaptation, reuse, and case-base maintenance, and then present a brief summary of six CBR applications that use soft computing techniques.

An Application of Genetic Algorithm for the Real-life Problems

2018 ◽  
Vol 11 (4) ◽  
pp. 178
Author(s):  
Santosh Kumar Suman ◽  
Awadhesh Kumar ◽  
Vinod Kumar Giri
Keyword(s):  
Genetic Algorithm ◽  
Real Life ◽  
The Real ◽  
Life Problems

scholarly journals Automatic Procedures as Help for Optimal Cam Design

2006 ◽  
Author(s):  
Massimo Antonini ◽  
Alberto Borboni ◽  
Roberto Bussola ◽  
Rodolfo Faglia
Keyword(s):  
Genetic Algorithm ◽  
Soft Computing ◽  
Design Process ◽  
Model Identification ◽  
Optimization Method ◽  
Realistic Model ◽  
Design Problems ◽  
Soft Computing Techniques ◽  
Cam Follower ◽  
Set Up

In this work we suggest a synthesis of recent results obtained on the application of soft-computing techniques to solve typical automatic machines design problems. Particularly, here we show an optimization method based on the application of a specialized algorithms ruled by a generalized software procedures, which appears able to help the mechanical designer in the first part of the design process, when he has to choose among different wide classes of solutions. In this frame, among the different problems studied, we refer here about the choice of the best class of motion profiles, to be imposed to a cam follower, which must satisfy prefixed design specifications. A realistic behaviour of the system is considered and the parameter model identification is set up by a soft computing procedure. The design, based on theoretical knowledge, sometimes is not sufficient to fulfil desired dynamical performances, in this situation, a residual optimization is achieved with the help of another optimizing method. The problem of a cam-follower design is presented. A class of motion profiles and the best theoretical motion profile is selected by an evolutionary algorithm. A realistic model is considered and its parameter identification is achieved by a genetic algorithm. The residual optimization is achieved by a servomotor optimized by another genetic algorithm. Evolutionary approach is used during all the design process and, as was shown, it allows really interesting performance in terms of simplicity of the design process and in terms of performance of the product.

scholarly journals Fuzzy Logic Based Teaching/Learning of a Foreign Language in Multilingual Situations

2017 ◽  
Vol 7 (2) ◽  
pp. 71-84 ◽  
Author(s):  
Sweta SINHA
Keyword(s):  
Fuzzy Logic ◽  
Mother Tongue ◽  
Real Life ◽  
Efficient Solutions ◽  
Linguistic Knowledge ◽  
Indian Language ◽  
Natural Languages ◽  
Technical Students ◽  
Life Problems ◽  
Teaching Learning

The concept of Fuzzy Logic (FL) has gained momentum in areas of artificial intelligence and allied researches because of its absolute ability to present efficient solutions to real life problems. Contrary to the paradigmatic approach to the solutions of being either absolutely true or false [0 or 1] the fuzzy sets provide a range of possible outputs with error prone inputs which are vague and inaccurate using linguistic objects instead of mere mathematical numbers. A multilingual situation poses a similar challenge for a language teacher/learner where languages exist in continuum. Learners with heavy mother tongue influence tend to use their natural languages instinctively in a way that can create their own fuzzy rules to encounter the situation of being taught an entirely new language. A typical Indian language classroom is highly multilingual where scope of errors is numerous though they are ignored. This leads to stress both for the teachers as well as the learners making the classroom ambience more mechanistic than human. To combat such situations FL based Three-Phase Model of language teaching has been proposed which derives its basis on the presumption that the language instructor is aware of general rules of linguistics. An empirical longitudinal study on 150 undergraduate technical students designed on the proposed framework has been conducted to establish the efficiency and the success of the model. Observing language pedagogy through the lens of fuzzy logic and fuzzy thinking will not only make the classroom more real-like but it will also tap the pre-existing linguistic knowledge of the learners. Language interference will be more of a resource than a challenge.

scholarly journals Applicability of Cellular Automata in Cryptanalysis

Cryptography ◽  
2020 ◽  
pp. 180-191
Author(s):  
Harsh Bhasin ◽  
Naved Alam
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Cellular Automata ◽  
Literature Review ◽  
Soft Computing ◽  
Search Problem ◽  
Extensive Literature ◽  
Soft Computing Techniques ◽  
A New Technique ◽  
The Given

Cryptanalysis refers to finding the plaintext from the given cipher text. The problem reduces to finding the correct key from a set of possible keys, which is basically a search problem. Many researchers have put in a lot of effort to accomplish this task. Most of the efforts used conventional techniques. However, soft computing techniques like Genetic Algorithms are generally good in optimized search, though the applicability of such techniques to cryptanalysis is still a contentious point. This work carries out an extensive literature review of the cryptanalysis techniques, finds the gaps there in, in order to put the proposed technique in the perspective. The work also finds the applicability of Cellular Automata in cryptanalysis. A new technique has been proposed and verified for texts of around 1000 words. Each text is encrypted 10 times and then decrypted using the proposed technique. The work has also been compared with that employing Genetic Algorithm. The experiments carried out prove the veracity of the technique and paves way of Cellular automata in cryptanalysis. The paper also discusses the future scope of the work.

scholarly journals Performance Analysis of Genetic Algorithm, Particle Swarm Optimization and Ant Colony Optimization for solving the Travelling Salesman Problem

2019 ◽  
Vol 8 (2S4) ◽  
pp. 91-95
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Ant Colony Optimization ◽  
Soft Computing ◽  
Travelling Salesman Problem ◽  
Particle Swarm ◽  
Ant Colony ◽  
Travelling Salesman ◽  
Swarm Optimization ◽  
Soft Computing Techniques

The Travelling salesman problem also popularly known as the TSP, which is the most classical combinatorial optimization problem. It is the most diligently read and an NP hard problem in the field of optimization. When the less number of cities is present, TSP is solved very easily but as the number of cities increases it gets more and more harder to figure out. This is due to a large amount of computation time is required. So in order to solve such large sized problems which contain millions of cities to traverse, various soft computing techniques can be used. In this paper, we discuss the use of different soft computing techniques like Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO) and etc. to solve TSP.

A Fuzzy Based Approach for Empirical Analysis of Unstructured Data

2020 ◽  
Vol 17 (9) ◽  
pp. 4375-4379
Author(s):  
Mausumi Goswami ◽  
B. S. Purkayastha
Keyword(s):  
Fuzzy Logic ◽  
Empirical Analysis ◽  
Soft Computing ◽  
Engineering Problem ◽  
Data Uncertainty ◽  
Natural Languages ◽  
Text Data ◽  
Random Uncertainty ◽  
Soft Computing Techniques ◽  
Set Membership

Computational intelligence and soft computing has many promising technologies such as Text Mining. Document Classification using soft computing techniques like fuzzy logic helps to find a more practical solution due to ambiguity and uncertainty present in the text data. Uncertainty and information may be reflected as the part and parcel of any industrial or engineering problem to be solved. Information refers to the facts required to solve it and uncertainty refers to the non-random lack of certainty (‘non-random uncertainty’), ambiguity, haziness in the system. It is very important to ponder on the nature of uncertainty involved in a problem. Father of fuzzy logic, Lofti Zadeh (1965) suggested that decision-making using set membership is the key when it is required to deal with uncertainty. Fuzzy clustering helps to identify patterns which are difficult to be discovered using crisp clustering. Natural languages contain non-random uncertainty. To deal with non-random uncertainty or different degrees of truth or partial truth Fuzzy logic may be used. This work focuses on fuzzy logic based approaches being utilized for identification of coherent patterns. Empirical Analysis are conducted to realize and evaluate the effect of the methodology proposed.

Prediction of cutting tool life based on Taguchi approach with fuzzy logic and support vector regression techniques

2015 ◽  
Vol 32 (3) ◽  
pp. 270-290 ◽  
Author(s):  
Jaganathan Gokulachandran ◽  
K. Mohandas
Keyword(s):  
Fuzzy Logic ◽  
Soft Computing ◽  
Tool Life ◽  
Cutting Tool ◽  
Support Vector ◽  
Taguchi Approach ◽  
Content Type ◽  
Neuro Fuzzy ◽  
Soft Computing Techniques ◽  
Life Values

Purpose – The accurate assessment of tool life of any given tool is a great significance in any manufacturing industry. The purpose of this paper is to predict the life of a cutting tool, in order to help decision making of the next scheduled replacement of tool and improve productivity. Design/methodology/approach – This paper reports the use of two soft computing techniques, namely, neuro-fuzzy logic and support vector regression (SVR) techniques for the assessment of cutting tools. In this work, experiments are conducted based on Taguchi approach and tool life values are obtained. Findings – The analysis is carried out using the two soft computing techniques. Tool life values are predicted using aforesaid techniques and these values are compared. Practical implications – The proposed approaches are relatively simple and can be implemented easily by using software like MATLAB and Weka. Originality/value – The proposed methodology compares neuro – fuzzy logic and SVR techniques.

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