Mutation is NEVER NECESSARY for finding optimal solutions to a problem. True False
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Mutation is NEVER NECESSARY for finding optimal solutions to a problem.
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- Even the tiniest activities may be made easier using the Spiral Model.How would you recommend fixing a Genetic Algorithm's local solution issue so that it could find a global optimum solution?Crossover and Mutation The two main operations in evolutionary computing are crossover and mutation. Crossover works like this: Randomly choose two parents from the population. Let’s say these: Parent 1: T F T F T T F Parent 2: T T T F F T T Those two parents will create a child whose DNA is related to the parents’. It works like this: for each of the seven genes in the chromosome, we will randomly pick a number between 1 and 10 and use it to choose which parents’ value the child will get. If the random number is 1 through 5, we will use Parent 1’s included value for the child; if it is 6…
- Crossover and Mutation The two main operations in evolutionary computing are crossover and mutation. Crossover works like this: Randomly choose two parents from the population. Let’s say these: Parent 1: T F T F T T F Parent 2: T T T F F T T Those two parents will create a child whose DNA is related to the parents’. It works like this: for each of the seven genes in the chromosome, we will randomly pick a number between 1 and 10 and use it to choose which parents’ value the child will get. If the random number is 1 through 5, we will use Parent 1’s included value for the child; if it is 6…The following is a collection of current research publications that make use of techniques associated with machine learning.Recursive filtering techniques are often used to reduce the computational complexity of a repeated operation such as filtering. If an image filter is applied to each location in an image, a (horizontally) recursive formulation of the filtering operation expresses the result at location (x +1, y) in terms of the previously computed result at location (x, y). A box convolution filter, B, which has coefficients equal to one inside a rectangular win- dow, and zero elsewhere is given by: w-1h-1 B(r, y,w, h) = ΣΣΤ+ i,y + ) i=0 j=0 where I(r, y) is the pixel intensity of image I at (x, y). We can speed up the computation of arbitrary sized box filters using recursion as described above. In this problem, you will derive the procedure to do this. (a) The function J at location (x,y) is defined to be the sum of the pixel values above and to the left of (x,y), inclusive: J(r, y) = - ΣΣ14.0 i=0 j=0 Formulate a recursion to compute J(r, y). Assume that I(r, y) = 0 if r <0 or y < 0. Hint: It may be…
- Briefly explain the roulette wheel scheme’s major shortcoming in genetic algorithms.A Python language Programming in Natural Language Many researchers today now use data from Twitter to analyze and predict the future events. Questions such as which place in a country is the happiest one, who will be the next US president and which place has the highest rate of depressed people, sometimes depend on the information extracted from thousands of tweets. In case of predicting the happiest state in the US, NLP experts have a set of words that also contains their rates, respectively. For example, the word “great” may have a rate from a scale of 1 to 10, 10; the word "awesome" may have a rate of 8; the word “sad” may have a rate 1 and so on. By computing the average score of a tweet using this set of words, researchers would now be able to measure and categorize the mood of a tweet depending on a certain threshold. In this problem, you will be an assistant of an NLP expert who will determine the mood of a tweet. The category would be: < 5 is "sad" >= 5 is "happy" Let…is....... a process of looking for the best sequence is called solution problem Path search
- The use of computers in education is referred to as computer-assisted instruction (CAI). One problem that develops in CAI environments is student fatigue. This problem can be eliminated by varying the computer's dialogue to hold the student's attention. For each correct answer and each incorrect an- swer. The set of responses for correct answers is as follows: Very good! Excellent! Nice work! Keep up the good work! The set of responses for incorrect answers is as follows: No. Please try again. Wrong. Try once more. Don't give up!No. Keep trying. Use random number generation to choose a number from 1 to 4 that will be used to select an appropriate response to each answer. Use a switch statement to issue the responses. Please write the code in Javascript HTML5The term "dynamic programming" refers to a mathematical optimization method that involves breaking down a complex problem into smaller subproblems and solving them recursively.Devon designs a computer algorithm that gives users a movie recommendation based on information entered into a viewer profile. Users are asked to rate the recommendation as either "good" or "bad." After testing the algorithm, Devon concludes that the algorithm offers good movie recommendations in 87% of all cases, with a 3% margin of error. Devon expects the algorithm to offer approximately 5,000 movie recommendations this month, and he wants to calculate the number of recommendations that are expected to be "good." What would the likely range of "good" recommendations be? A. 1,400 to 4,550 good recommendations B. 4,100 to 4,550 good recommendations C.4,200 to 4,500 good recommendations D. 4,285 to 4,459 good recommendations
