to accomplishing this goal are neural networks and fuzzy logic control systems. This paper will only concern itself with the latter. Fuzzy logic control systems are designed to mimic the approximate reasoning of human thinking and decision making. Instead of standard computer logic, which is based on only 1’s and 0’s or true and false, fuzzy logic is based on a more loose set of linguistic rules that are called the knowledge base. The fuzzy control system is designed to mimic the effects of
. The Fuzzy Logic is a form of a systematic reasoning that can be integrated into automation systems with classical human reasoning schemes. Fuzzy theory was first suggested and probed by Prof Zadeh in 1965 [11] Fuzzy systems are apprehension based or rule based systems. The heart of a fuzzy system is a knowledge base inherent of the so-called If-Then rules. After allocating the fuzzy sets and their membership functions, rules must be noted to place an action to be taken for each combination of
so night temporary blindness started due to which the accident occurred, in order to reduce the temporary blindness they started making the system automated. In 1998 Fuzzy control of head-light intensity of automobiles: design approach was proposed to control the intensity of the head light .Fuzzy logic is a form of many-valued logic in which the truth values of variables may be any real number between 0 and 1.But the drawback was it could only be used in controllers and would never be successfully
of which five are universal and the sixth one is used specifically for different applications. Prediction of RMR by the use of fuzzy logic makes it easier to predict the rating of rock more or less the same as calculated from experimental data. It becomes of great importance at the moment when we don’t have the rating tables of the six parameters, then by the use of fuzzy membership functions, we can approximately predict the RMR of the rock. Introduction While working on fields, it is impossible
Mind and Machine: The Essay Technology has traditionally evolved as the result of human needs. Invention, when prized and rewarded, will invariably rise-up to meet the free market demands of society. It is in this realm that Artificial Intelligence research and the resultant expert systems have been forged. Much of the material that relates to the field of Artificial Intelligence deals with human psychology and the nature of consciousness. Exhaustive debate on consciousness and the possibilities
are investigated and used, are: • Artificial Neural Network • Expert Systems • Genetic Algorithms • Fuzzy Logic • Artificial Life • Natural Language Processing • Robotics • Voice and Face Recognition (Tektaş, 2010). 4.1. Artificial Intelligence Based on Fuzzy Logic Fuzzy logic is a subject in its own right as a mathematical; also it is a subunit of artificial intelligence. The aim of fuzzy logic is, to draw conclusions closer to life by modelling human’s t... ... middle of paper ... ...identified
Drought is a multi-causal and complex environmental issue, and can have serious socioeconomic consequences. Recently, IPCC (the Intergovernmental Panel on Climate Change) in Fourth Assessment Report (AR4) concluded that South Asia and the Middle East would experience sever, prolonged droughts as a result of global climate changes, explicitly the increase in greenhouse gases in the atmosphere (IPCC, 2007). Drought is a weather-related natural disaster whose effect is aggravated by human activities
it is quite hot area for researchers to build such a system so that people can get out of these problems, and successfully they have implemented so far an intelligent system, which is mostly based on fuzzy logic technology to manage control traffic lights. Figure 2.1: The simulated fuzzy logic traffic control system Limitations: • By implementing such a system it requires a high cost Ratio. • Accuracy of the same system can be increased by using PLC based system. • Highly chance of error
Classification as an essential data mining technique used to develop models describing different soil classes. Such analysis can present us with a complete understanding of various soil databases at large. In our study, we proposed a novel Neuro-fuzzy classification based technique and applied it to large soil databases to find out significant relationships. We used our technique to three benchmark data sets from the UCI machine learning repository for soil categorization and they were namely Statlog
Expert Systems: The Past, Present and Future of Knowledge-based Systems Expert Systems were invented as a way to decrease the reliance by corporations on human "experts" -- people who apply reasoning and experience to make judgements in a specific field, such as medicine, insurance underwriting or the operation of a power-plant. Hence, an expert system should include a database of facts and a way of reasoning about them. In many, but not all, applications it is also helpful to have a way for
world. Detection and analysis of the disease is a significant part of data mining research. Classification as an essential data mining procedure also helps in clinical diagnosis and analysis of this disease. In our study, we proposed a novel Neuro-fuzzy classification based method. We applied our method to three benchmark data sets from the UCI machine learning repository for detection of breast cancer; they were namely Wisconsin Breast Cancer (WBC), Wisconsin Diagnostic Breast Cancer (WDBC), and
Hollow Words in Winesburg, Ohio Sherwood Anderson, in his masterpiece Winesburg, Ohio was writing against the notion that stories have to have a plot which reveals a moral idea or conclusion. Like the "tales" that Doctor Parcival tells George Willard in "The Philosopher," Anderson's short stories also seem to "begin nowhere and end nowhere" (51). We as readers must, like George Willard, decide if such stories are little more than "a pack of lies" or if rather, "they contain the
Middleton Mutual is a large insurance company that is seeking innovation. The Chief Information Officer, Dennis Devereaux, and Vice President of Information Systems, Max Vargo, are trying to push for a new expert system to ease up the underwriting process of their company. The issue that arises in the company is that certain higher ups aren’t willing to fund this one million dollar project without proof of return. Within the next year, the company will be losing two underwriters. Devereaux has his
Support communications? Why or why not? Advantages and disadvantages are an equal part of Expert Systems and ROI analyses; however, each is based on circumstances based on each unique case. One main shortcoming of the ROI analysis is the strong base on statistical analysis which may fail to recognize certain areas of opportunity not explored. Previously stated, the Expert System was used to interact directly with a broad range of students and exceeded its original purpose by providing more marketing
B. Naïve Bayesian Classification In machine learning, Naive Bayesian Classification is a family of a simple probabilistic classifier based on the Bayes theorem (or Bayes’s rule) with Naive (Strong) independence assumption between the features. It is one of the most efficient and effective classification algorithms and represents a supervised learning method as well as a statistical method for classification. Naïve Bayesian classifiers assume that the effect of an attribute value on a given class
this paper a fuzzy logic based approach is presented to assist organizations in making the decision regarding which software development methodology to select from Rational Unified
Neural Networks, Special issue on Data Mining and Knowledge Representation (2000). [17] Mutanen,Teemu. Customer churn analysis- a case study, Research Report VTTR0118406, March 15, 2006. [18] De Oliveira, J.V., Pedrycz W. (editors) (2007) Advances in Fuzzy Clustering and its Applications, John Wiley & Sons Ltd. [19] J. Hadden, A. Tiwari, R. Roy, and D. Ruta. Churn Prediction using Complaints Data. International Journal of Intelligent Technology, 13:158{163, May 2006. [20] H. Van Khuu, H.-KieLee, and
My guiding principle has been my passion to keep learning about and using Computers and Mathematics. Having a profound interest in discrete mathematics, I have always wanted to work on logic and that is the major reason for me to choose Computing. During my A-levels, I learned Visual Basic independently and how logic can be utilized for problem solving in any complex scenario. I also implemented these useful VB codes into my AS ICT coursework for which I received 97%. The puzzle-solving aspect of mathematics
obstacles to the attainment of true, certain, or precise knowledge about things and events. After analysing the ontological, logical, and axiological status of indeterminary, I outline the aoristic logic which allows adequate descriptions of phenomena pertaining to an area of indeterminary. Aoristic logic provides a propositional calculus that makes possible the compatibility of order with indeterminacy. 1. Argument Truth, certainty, precision are the highest criteria for judgement on any statement
use of a method and the application of a procedure play within any conceptual process: communicable by virtue of the codes and the prescribed norms, comparable in every time and place by virtue of the reproducibility of the procedures. Euclidian logic begins with the inductive definition of very simple concepts and gradually constructs a vast body of results, organised in such a way so that each concept depends on the previous. Thus, a strong and rigorous construction is derived that makes all operations