is fuzzy logic an algorithm?
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Fuzzy logic algorithm helps to solve a problem after considering all available data. Then it takes the best possible decision for the given the input. The FL method imitates the way of decision making in a human which consider all the possibilities between digital values T and F. What Is Fuzzy Logic?
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Soft computing, as opposed to traditional computing, deals with approximate models and gives solutions to complex real-life problems. ... Soft computing is based on techniques such as fuzzy logic, genetic algorithms, artificial neural networks, machine learning, and expert systems.
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In computer science an algorithm still is a step-by-step manner towards solving a problem - an implementation-agnostic set of steps. A method commonly refers to a chunk of code associated with a class or object that does some task - it can implement many algorithms potentially.
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Fuzzy logic is a rule-based system that can rely on the practical experience of an operator, particularly useful to capture experienced operator knowledge. Fuzzy logic is a form of artificial intelligence software; therefore, it would be considered a subset of AI. ... It's not as fuzzy as you might think.
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['Precision – the steps are precisely stated(defined).', 'Uniqueness – results of each step are uniquely definedand only depend on the input and the result of the precedingsteps.', 'Finiteness – the algorithm stops after a finite number ofinstructions are executed.', 'Input – the algorithm receives input.']
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Specific time series analysis techniques suitable for forecasting, like ARIMA models or Exponential Smoothing, could certainly be called "learning algorithms" and be considered part of machine learning (ML) just as for regression. They simply rarely are.
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Consistent and Admissible Heuristics. Any consistent heuristic is also admissible.
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Inductive reasoning does not guarantee a true result, but it does provide a means of making a conjecture. With deductive reasoning, we use general statements and apply them to spe- cific situations.
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Yes It is. Using millions of if-else statements in your code means you're already aware of those if-else conditions and you're writing a program to tackle the situation. AI on the other hand in simple words means a program taking care of the other scenarios too which it is NOT programmed for.
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Logic OR Function. The Logic OR Function function states that an output action will become TRUE if either one “OR” more events are TRUE, but the order at which they occur is unimportant as it does not affect the final result. For example, A + B = B + A.
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An ALGORITHM is a sequence of moves that you need to do in a specific order. When following the algorithms in this guide, it is important to maintain the FRONT face of your Rubik's Cube so it stays the FRONT through all of the turns.
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The NGram class extends the Python 'set' class with efficient fuzzy search for members by means of an N-gram similarity measure. ... The N-grams are character based not word-based, and the class does not implement a language model, merely searching for members by string similarity.
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Fuzzy models or sets are mathematical means of representing vagueness and imprecise information (hence the term fuzzy). These models have the capability of recognising, representing, manipulating, interpreting, and utilising data and information that are vague and lack certainty.
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Algorithms are usually build on logic in order to make logical decision. ... But more important algorithms perform operations on data usually. Algorithms can have various length, being more or less complex.
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['Brute-force or exhaustive search.', 'Divide and Conquer.', 'Greedy Algorithms.', 'Dynamic Programming.', 'Branch and Bound Algorithm.', 'Randomized Algorithm.', 'Backtracking.']
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To say algorithms control the stock market is not really correct. Algorithms written by people certainly do affect the behavior of the stock market and many other markets where rules are codified and computers can be programmed to make decisions based on the rules.
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The formalism of linguistic variables and fuzzy if–then rules is, in effect, a powerful modeling language which is widely used in applications of fuzzy logic. Basically, the formalism serves as a means of summarization and information compression through the use of granulation.