The Fuzzy Logic System

Knight, G., Roosa, M., Calderon-Tina, C., & Gonzales, N (2009), J. (2009). Methodological issues and research on Latino populations, In L. Sayas & J. Borrego, Jr. (Eds.) Handbook of U.S. Latino psychology: Development and community based perspectives (pp.45-62).

A Power system is an connection of generators to load centres. Through H.V. electrical lines & in general is controlled mechanically. It can be divided into 3 subsystems: Generation, X’mission and Distribution-systems. The electric power demand is Growing and building of new generating units & transmission circuits is becoming difficult because of environmental & economic reasons. So, power utilities are forced to depend on utilization of existing generating units and to load existing lines close to their heating limits.

For a perfectly planned power grid, the power generation of each region is matched with the power consumption within this region, so that the power lines will always carry a reasonable workload. If one power line fails to work, other parallel lines would have to carry extra power, which is bad for safety and may lead to fire. The power system operators are the ones

Expert systems are also known as knowledge based systems. These systems rely on a basic set of rules for solving specific problems and are capable of learning. The laws are defined for the system by experts and then implemented using if-then rules. These systems basically imitate the expert’s thoughts in solving the problem. An example of this is a system that diagnosis medical conditions. The doctor would input the symptoms to the computer system and it would then ask more questions if need or give diagnoses. Other examples include banking systems for acceptance of loans, advanced calculators, and weather predictions.

Artificial intelligence or AI is in simple terms, the ability for a computer to learn on its own, without any input from the user, and it has the ability to think on its own and make its own decisions and is also able to understand human intelligence. This is done by using tools in many fields. These fields include, but are not limited to computer science, natural language and speech, machine learning and patter recognition, and computer vision (Luke Muehlhauser, 2014). This also includes psychology, cognitive science, neuroscience, economics, probability, and optimization and logic. These are only the beginnings of what is required to meet what is needed to even to begin to scratch the topic of

ABSTRACT- An Artificial Neural Network (ANN) is an information processing paradigm that is inspired by the way biological nervous systems, such as the brain, process information [1]. Artificial Neural Networks (ANN) also called neuro-computing, or parallel distributed processing (PDP), provide an alternative approach to be applied to problems where the algorithmic and symbolic approaches are not well suited. The objective of the neural network is to transform the inputs into meaningful outputs. There are many researches which show that brain store information as pattern. Some of these patterns are very complicated and allows us to recognize from different angles. This paper gives a review of the artificial neural network and analyses the techniques in terms of performance.

Fuzzy system has been applied to various type of application or system. Fuzzy system is an approach of the computational intelligence use a collection of fuzzy functions and rules to reason about a data. Its use any Fuzzy Logic based system which use Fuzzy Logic as basic for knowledgeable representation using different forms of knowledge. The main function of fuzzy logic technology is it ability of propose an approximate solvent to an imprecisely formulated problem. Fuzzy Logic in other meaning can be said as a procedure paradigm that is based on how human was thinking. What can be said that fuzzy logic is closer to human reasoning than the classical logic. Where then it attempts to precisely formulate and exactly solve a mathematical

In IT Foundations, I was assigned by Mrs. Baumaster to watch the video Fuzzy Thinking. The speaker in this video is an Astrophysicist by the name of Neil deGrasse Tyson. In the video, Fuzzy Thinking he talked about many things like what was wrong with the misspellings of the word Cat and about his choice between hiring two workers. The video did not seem very interesting at first but as I watched it, the video got more and more interesting. Tyson is a very good presenter in the video because he made it interesting and fun to listen to him. All in all, this video was a great way to get his message out on how people think.

In a narrow sense, fuzzy logic can be defined as a logical system, which is an expansion of multi-valued logic. Whereas in a wider sense it is almost similar with fuzzy sets theory. It is a method for computing based on "degrees of truth or fact" rather than the "true or false" (1 or 0). The idea of fuzzy logic was first proposed by Dr. Lotfi Zadeh of the University of California at Berkeley in the 1965 [65].

L.A. Zadeh, Fuzzy Sets [33] In 1965 the concept of fuzzy logic was first introduced by the Professor Lotfi A. Zadeh in the University of California, Berkeley [33]. Fuzzy logic is a powerful design system for implementing the artificial intelligence in the controller which provides simple and intuitive method for software engineers to implement logic in complex systems. This concept had been given in one amongst his research papers under the name Fuzzy logic or Fuzzy sets.

The decision making with multiple criteria (MCDM) has been successfully used in complex business problems. There are several methods for MCDM, such as Analytic Hierarchy process (AHP), Potentially All Pairwise Rankings of All Possible Alternatives (PAPRIKA), Weighted Sum Mode (WSM), Analytic network process (ANP), Multi-Attribute Utility Theory (MAUT) and so forth.

Sustainable development demands that the world must move towards a more sustainable energy future. CO2 Capture and Storage (CCS) has emerged as a new advance energy technology to facilitate this transition in addition to renewable energy. There are socio-technical uncertainties hampering the deployment of this energy system which is very complex to model. In this paper, our focus is on uncertainties regarding public acceptance. It is widely accepted in the literature that people’s decisions (especially those of lay stakeholders) towards CCS, are fuzzy, imprecise and ambiguous. The literature of the field, even reports that at one point the decision is stable, and at another it is unstable—clearly an inherent problem in the dialogue surrounding this topic and predicting these behaviors presents a tremendous mathematical challenge. In this paper, we have made the first attempt to explore the theoretical feasibility of fuzzy sets in modeling these socio-technological uncertainties. Using this hard science method, we have proposed a new viewpoint that improves, but also deviates from the existing predictive methodologies our colleagues have adopted in modeling and predicting stakeholders’ complex decision-making behaviors. Using eight key socio-technical parameters, we have proposed a design of a novel human intelligence model based on fuzzy logic, for predicting these complex human behaviors on CCS life cycle. The data used in modeling the proposed system

The purpose of this report is to give information on the subject known as Logical reasoning and its use in Computer Science and computers in general. A historical background behind logic and Logical reasoning is firstly given, followed by an overview of the modern subject and the types it’s divided into. The types are then explained. The overlap between the field of logic and that of computer science is also given an explanation. The report ends with a brief overview on the subject and its tie to computer science and computing.

ABSTRACT: In this paper, we study some of the properties of multi intuitionistic fuzzy rw-continuous mappings and multi intuitionistic fuzzy rw-irresolute mappings in multi intuitionistic fuzzy topological spaces and prove some results on these.

This system is divided in a knowledge base and inference rules. In the video, this system is used when it comes the control center. The employees are checking flights and regulating flows thanks to precious information given in their computer like the weather, the flow rate and a packaging monitoring.