Fuzzy Systems and Machine Intelligence Abstract: Our natural language is perhaps the most powerful form of communicating information for any given problem or situation. Combining natural language and numerical information into fuzzy systems provides the framework to represent knowledge, constraints and inference procedures. Fuzzy systems provide advantages in the development of systems solutions that perform tasks such as automatic modeling, prediction, pattern recognition, and optimal decision making, control and planning. With this, fuzzy systems are an essential tool for industrial and manufacturing systems engineering. Fuzzy logic is a different approach to representing uncertainty - it emphasizes the double meanings of …show more content…
It is an extension of the kind of logic that enables computers to make decisions from imprecise and inexact information. With it, computers become able to represent, manipulate, and interpret such descriptions as "a little", "bigger", or "average", and use the differences between them to perform complicated tasks. One of the greatest benefits of fuzzy logic is simple and uncomplicated programming. Fuzzy logic is proving to be the fastest and easiest way to automate costly applications using a tight, closed-loop control. In addition, it produces better and more elegant solutions such as energy savings and a reduction of wear and tear on system hardware. Some manufacturers maintain that fuzzy logic cuts software development time for control applications by a factor of ten - which is a major benefit in highly competitive industries such as consumer electronics. Fuzzy logic also offers a way to perform tasks that are very difficult or expensive to do with strict digital logic. For example, fuzzy logic can help automate tasks that call for comparing inputs from multiple sources, or making decisions within conflicting facts, such as a requirement that a railroad engine be able to accelerate quickly as well as evenly. Fuzzy logic is also a highly robust method that works with inputs that lack …show more content…
They are used in several wide-ranging fields, including Linear and Nonlinear Fuzzy Control, Pattern Recognition, Financial Systems, Operation Research, and Data Analysis. The purpose of Fuzzy Control is to influence the behavior of a system by changing an input (or inputs) to that system according to a rule or set of rules that model how that system operates. The system being controlled may be mechanical, electrical, chemical or any combination of these. Historically, control theory uses a mathematical model to define a relationship that changes the desired state and observed state of the system into an input or inputs that will alter the future state of that system. The most common example of a fuzzy control model is the PID (proportional-integral-derivative) controller. This takes the output of the system and compares it with the desired state of the system and adjusts the input value based on the difference between the two values. Fuzzy control replaces the role of the mathematical model with another that is built from a number of smaller rules that in general, only describe a small section of the whole system. The process of inference binds them together to produce the desired outputs. In other words, a fuzzy model replaces the mathematical one. The inputs and outputs of the system have remained unchanged. Fuzzy sets and logic must be viewed as a formal mathematical theory for the representation
Noori, S., Feylizadeh, M. R., Bagherpour, M., Zorriassatine, F., & Parkin, R. M. (2008). Optimization of material requirement planning by fuzzy multi-objective linear programming. Proceedings of the Institution of Mechanical Engineers, 222, 887-900. Retrieved from http://search.proquest.com/docview/195144743?accountid=32521
... middle of paper ... ... In Intelligent Data Engineering and Automated Learning–IDEAL 2006 (pp. 1346-1357. Springer Berlin, Heidelberg.
The Passive Decision Support System, Active Decision Support System and Cooperative Decision Support System (2013). A Passive Decision Support System, is a system that assists in the process of decision making, however, it can’t bring out clear decisions (2013). An active Decision Support System, on the other hand, can bring out solutions and decision suggestions. The Cooperative Decision Support System allows the decision maker to change the decision suggestions provided by the system before the information is sent back to the system for validation (2013). While there are many ways computerized systems can be characterized, it is important to compare them in terms of what the user will be doing with the
...gic is based on uncertainties in traditional logic there is no place for uncertainties. Some technologic areas that fuzzy logic is used can be ordered like that:
The neural network is required because of the information being scanned, traded, shipped and pulled from inventory by robots and tracking systems to report to the customer as quickly as possible. We have learned examples of AI being used today such as Expert Systems, Neural Networks, Genetic Algorithms, Intelligent Agents and Virtual
"My name is Dorothy," said the girl, "and I am going to the Emerald City, to ask the Oz to send me back to Kansas."
Artificial intelligence(AI) is refer to as computer algorithms that show functions that represent intelligence or duplicate certain components and elements of intelligence (Novella, 2017). Computers are good at crunching numbers, running algorithms, recognizing patterns, and searching and matching data. Artificial intelligence is also defined as the stimulation of human intelligence, functioned or processed by machines, especially computer system (Rouse, 2016). These processes involved learning which means the acquisition of information and the rules for using the information, reasoning whereby using the rules to achieve approximate conclusions, and lastly is self-correction. AI has applications in almost every way we use computers in society (Smith, 2006).
Since high-quality decision-making plays such a significant role in our personal and professional lives, it's extremely important to identify tools and techniques that can aide us in the process. While many such tools exist, for the purposes of this paper, I will concentrate on one specific tool used for this purpose. The tool that will be discussed is called the "Six Thinking Hats" method (Mind Tools.com).
The case based reasoning system proposed here mimics the human decision making process by learning from previous experience and using the knowledge to solve current problem. This system will utilize previous adverse episodes and their solutions to prevent reoccurrences, and also to detect the oc...
Scientists claim that devices with Artificial Intelligence will replace office workers during next 5 years (Maksimova).According to this statement it is possible to say that AI has a great influence on humanity. Pursuant to Oxford Dictionary Artificial Intelligence or AI is the theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages(dictionary).Firstly, this research will analyze positive and negative impacts of development of Artificial Intelligence on economic sphere. Then, author going to discuss social effects of Artificial Intelligence. After the considering all perspectives that link to this topic, the last step will be to draw a conclusion.
Therefore, to determine the material handling system is very important for reduce cost and increased profits. The fact material handling systems represent a major part of the total manufacturing cost make necessity to choose adequately the material handling system when a manufacturing system is designed. One of the most successful applications of experts systems is selection of equipment for material handling (SEMH). SEMH lookups the knowledge bottom to be able to suggest the degree associated with mechanization, and also the type of product coping with equipment to become utilized, according to some traits. Fisher, Farber, and Kay (1998) have introduced MATHES: material handling equipment selection expert systems for the selection of a material handling equipment from 16 possible choices. MATHES as well as 172 principles takes course, product stream quantity, product sizing's in addition to distance concerning sectors because variables. Swaminathan, Matson, and Mellichamp (1992) have developed EXCITE: expert consultant for in-plant transportation equipment addressing 35 equipment
Artificial neural networks are systems implemented on computer systems as specialized hardware or sophisticated software that loosely model the learning and remembering functions of the human brain. They are an attempt to simulate the multiple layers of processing elements in the brain, called neurons. These elements are implemented in such a way so that the layers can learn from prior experience and remember their outputs. In this way, the system can learn to recognize certain patterns and situations and apply these to certain priorities and output appropriate results. These types of neural networks can be used in many important situations such as priority in an emergency room, for financial assistance, and any type of pattern recognition such as handwritten or text-to-speech recognition.
Artificial Intelligence is the scientific theory to advance the scientific understanding of the mechanisms underlying thought and intelligent behavior and their embodiment in machines. This is going to hold the key in the future. It has always fa...
AIS can greatly contribute to managing Value Chain of any manufacturing company and resulting in
Humans can expand their knowledge to adapt the changing environment. To do that they must “learn”. Learning can be simply defined as the acquisition of knowledge or skills through study, experience, or being taught. Although learning is an easy task for most of the people, to acquire new knowledge or skills from data is too hard and complicated for machines. Moreover, the intelligence level of a machine is directly relevant to its learning capability. The study of machine learning tries to deal with this complicated task. In other words, machine learning is the branch of artificial intelligence that tries to find an answer to this question: how to make computer learn?