Advantages Of Fuzzy Logic

Information is made from Data that is numerical which is changed and used to make it seem sense. For an example train timetable, the number of trains and how much it weights.

The objective of the neural network is to transform the input to meaningful output. Neural networks are often used for statistical analysis and data modeling. Neural network has many uses in data processing, robotics, and medical diagnosis [2]. From the starting of the neural network there are various types found, but each and every types has some advantages and disadvantages. Deep learning and -neural network software are the categories of artificial neural network. The parallel process also allows ANNs to process the large amount of data very efficiently. The artificial neural network is built with a systematic

Neural networks emulate the human brain’s neurons, which is a mesh-like network of interconnected processing components. This allows the system to process numerous pieces of information at the same time, and can learn to understand patterns within the processes, which it can use to solve related problems on its own. Examples include;

It is observed from Table 8 and Fig.3 that for each of the five data sets, the highest accuracy is achieved by applying NNGe and Simple Logistics on the feature subset by MLBFSS. The proposed algorithm achieves higher accuracy, lower RMSE, smallest number of selected features compared with other feature selection algorithms. So MLBFSS produces comparatively small number of features with high relevance and is faster as it follows filter method.

The generic term for symbolic formal systems like first-order logic, second-order logic and many-sorted logic or infinitary logic.

Logic can be defined as the study of the methods and principles of correct reasoning or arguments. Logic teaches the techniques and methods for the correctness of different kinds of reasoning. It helps to detect errors in reasoning by examining and analyzing the various reasons. Logic investigates and classifies the structure of statements and arguments, both through the study of formal systems of inferences and through the study of arguments in natural language. It deals only with propositions that are capable of being true and false. Modern logic descends mainly from the ancient Greek tradition. All three philosophers; Aristotle, Bertrand Russell, and Immanuel Kant theorized the question of what is logic.

For example, Whitehead and Snow came from different backgrounds and would not have been friends if Cholera did not exist. Additionally, Snow’s map would not have existed if London did not exist. Snow’s map lead to geographical based information systems (GIS) because it took a city and mapped out the number of deaths. GIS allows citizens to view a place and overlay data to find answers. An example of a GIS system is Google Maps because the program takes a map, and overlays data, such as traffic levels, to visually show results. However, the accuracy of the results depends on how frequently the data is

An Expert System is software that uses understanding clarification methods in areas where individuals would generally be checked. Each system is broken down in detailed problem fields. The disadvantage to this system is that the information of the fields is narrow.

}\}$ be the corresponding Fuzzy sets defined by the membership function $ \{\mu _{A}^{1},\mu _{A}^{2},\mu _{A}^{3}, . . .\mu _{A}^{m}\}$. The implication of the form $\left ( A,{T_{i}^{A}} \right )\rightarrow \left ( B,{T_{j}^{B}} \right )$ or $A\epsilon {F_{i}^{A}},B\epsilon {F_{j}^{B}}$ is a Fuzzy Association Rule.\\

I choose logic as one of my logic as one of my central concepts because it is a type of reasoning that is based off principles of validity. Logical reasoning can be divided into two sub categories, Deductive logic and

George J. Kilr and Bo Yuan [32] Fuzzy logic is a way to formalize the human decision capacity of imprecise reasoning, or approximate reasoning. Such type of reasoning represents the human ability to find out the reason approximately and judge

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.

In computing – programming there is almost always more than one solution to a problem and this is where Logical Reasoning used to. The main use of Logical Reasoning is to anticipate the outcomes of the algorithms that are designed to solve a problem, to help select the best solution. Consequently Logical reasoning is the systematic application of rules to problem solving and task completion. These rules could be mathematical, logical, programming, grammatical, engineering, scientific, story construction in fact anybody of rules based around a logical system.

Artificial intelligence techniques are increasingly enriching decision support through means as data delivery, analyzing data trends, providing forecasts, developing data consistency, information providing to the exploiter in the most appropriate forms and suggesting courses of action.

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.