An aircraft company has their flight data as shown in the table below, where a forward flight from A to B will take 4 miles and a return B to A will take 3 miles. A B C D A 4 3 1 B 3 3 C 3 3 3 D 2 5 2...


An aircraft company has their flight data as shown in the table below, where a forward flight


from A to B will take 4 miles and a return B to A will take 3 miles.


A B C D


A 4 3 1


B 3 3


C 3 3 3


D 2 5 2


11. With the above information provided, draw a graph for the data provided. Indicate the


weights on them.


12. Produce the adjacency matrix for your graph drawn


13. Find the shortest path in your graph and show the vertices and edges


SECTION C


An artificial intelligence system was design to forecastthe financial trading market and predict


change based on observed variables from the business environment. The variables to be observed


are


i. Population(A)


ii. Poverty rate(B)


iii. Inflation (C)


iv. Available resources(D)


Theses variables can affect each other or impact upon one another.


Below is a table of the variables with their effect on each other.


A B C C


A 0.1 0.3 0.3 0.3


B 0.2 0.2 0.2 0.4


C 0.2 0.5 0.1 0.2


D 0.1 0.2 0.2 0.5


14. Draw the Markov chain state diagram for the table above.


15. If interventions by government will yield the transition state matrix below, predict the future of


the economic state in the financial market.


A B C D


A 0.1 0.3 0.1 0.5


B 0.1 0.2 0.1 0.6


C 0.2 0.4 0.1 0.3


D 0.4 0.2 0.1 0.3


SECTION C<br>An artificial intelligence system was design to forecast the financial trading market and predict<br>change based on observed variables from the business environment. The variables to be observed<br>are<br>i. Population(A) ii. Poverty<br>rate(B) iii. Inflation (C) iv.<br>Available resources(D)<br>Theses variables can affect each other or impact upon one another. Below<br>is a table of the variables with their effect on each other.<br>A<br>B<br>0.1<br>0.3<br>0.3<br>0.3<br>0.2<br>0.2<br>0.2<br>0.4<br>C<br>0.2<br>0,5<br>0.1<br>0.2<br>D<br>0.1<br>0.2<br>0.2<br>0.5<br>14. Draw the Markov chain state diagram for the table above.<br>15. If interventions by government will yield the transition state matrix below, predict the future of<br>the economic state in the financial market.<br>A<br>B<br>C<br>A<br>0.1<br>0.3<br>0.1<br>0.5<br>B<br>0.1<br>0.2<br>0.1<br>0,6<br>0.2<br>0.4<br>0.1<br>0.3<br>D<br>0.4<br>0.2<br>0.1<br>0.3<br>Examiner's Name: Dr Quist-Aphetsi Kester<br>-.2/3<br>16. Draw the state diagram for the results obtained from question 15.<br>SECTION B<br>An artificial intelligence neural system has two inputs at the entrance layer and 5 output nodes as<br>a result of an implementation of a fuzzy classifier. What is the fuzzy set for the 5 output values?<br>Zym<br>y(1)<br>R,<br>y(2)<br>T(°C)<br>+ Rah<br>y(3)<br>Iph<br>G (W/m)<br>y(4)<br>+ I,<br>y(5)<br>Entrance layer<br>Hidden layer<br>Output layer<br>

Extracted text: SECTION C An artificial intelligence system was design to forecast the financial trading market and predict change based on observed variables from the business environment. The variables to be observed are i. Population(A) ii. Poverty rate(B) iii. Inflation (C) iv. Available resources(D) Theses variables can affect each other or impact upon one another. Below is a table of the variables with their effect on each other. A B 0.1 0.3 0.3 0.3 0.2 0.2 0.2 0.4 C 0.2 0,5 0.1 0.2 D 0.1 0.2 0.2 0.5 14. Draw the Markov chain state diagram for the table above. 15. If interventions by government will yield the transition state matrix below, predict the future of the economic state in the financial market. A B C A 0.1 0.3 0.1 0.5 B 0.1 0.2 0.1 0,6 0.2 0.4 0.1 0.3 D 0.4 0.2 0.1 0.3 Examiner's Name: Dr Quist-Aphetsi Kester -.2/3 16. Draw the state diagram for the results obtained from question 15. SECTION B An artificial intelligence neural system has two inputs at the entrance layer and 5 output nodes as a result of an implementation of a fuzzy classifier. What is the fuzzy set for the 5 output values? Zym y(1) R, y(2) T(°C) + Rah y(3) Iph G (W/m) y(4) + I, y(5) Entrance layer Hidden layer Output layer
SECTION A<br>Arobotic machine's software uses Bayesian filter to measure its intelligence in processing legal<br>cases to determine whether a judgement made by judges are fair or not. A set of cases were fed into<br>the memory of the robot for processing in determining fairness. Let P (J) =0.25 be the probability<br>of cases brought to the courts with judgement made. Let P(E/J) =0.33 be the probability that a case<br>that was judged was based on evidences presented before the court. Let P (E/J') =0.87 be the<br>probability that some evidences were not used in the judgement even though they were resented<br>before the court.<br>Assuming you are part of the research team that induces the intelligence into the machine, solve<br>the following questions below.<br>1. Draw the Bayesian Network diagram in a form of a tree diagram to form the basis of<br>reasoning for the machine for the above situation.<br>2. Calculate for the probability for the cases for which judgement has not been passed P (J').<br>3. What is the probability for the cases for which judgement has not been passed and has no<br>considerable number of evidences P(E'/J')?<br>4. What is the probability for the cases for which judgement were made on but did not account<br>for the evidences filed against the accused. P (E'/J)?<br>5. What will be the total probability of evidence of presented cases in the courteven if they<br>are considerable but were not considered and also not considerable but were considered.<br>P(E)?<br>6. What will be the total probability of evidence not presented in all casesP(E')?<br>7. What will be the total probability of P(J'/E)?<br>8. What will be the total probability of P(J/E)?<br>9. What will be the total probability of P(J'/E')?<br>10. What will be the total probability of P(J/E')?<br>Examiner 's Name: Dr Quist-Aphetsi Kester<br>-.1/3<br>SECTION B<br>An aircraft company has their flight data as shown in the table below, where a forward flight from<br>A to B will take 4 miles and a return B to A will take 3 miles.<br>A<br>В<br>D<br>A<br>4<br>3<br>1<br>3<br>3<br>3<br>3<br>D<br>2<br>11. With the above information provided, draw a graph for the data provided. Indicate the<br>weights on them.<br>12. Produce the adjacency matrix for your graph drawn<br>13. Find the shortest path in your graph and show the vertices and edges<br>SECTION C<br>An artificial intelligence system was design to forecast the financial trading market and predict<br>change based on observed variables from the business environment. The variables to be observed<br>are<br>i. Population(A) ii. Poverty<br>rate(B) iii. hflation (C) iv.<br>Available resources(D)<br>Theses variables can affect each other or impact upon one another. Below<br>is a table of the variables with their effect on each other.<br>

Extracted text: SECTION A Arobotic machine's software uses Bayesian filter to measure its intelligence in processing legal cases to determine whether a judgement made by judges are fair or not. A set of cases were fed into the memory of the robot for processing in determining fairness. Let P (J) =0.25 be the probability of cases brought to the courts with judgement made. Let P(E/J) =0.33 be the probability that a case that was judged was based on evidences presented before the court. Let P (E/J') =0.87 be the probability that some evidences were not used in the judgement even though they were resented before the court. Assuming you are part of the research team that induces the intelligence into the machine, solve the following questions below. 1. Draw the Bayesian Network diagram in a form of a tree diagram to form the basis of reasoning for the machine for the above situation. 2. Calculate for the probability for the cases for which judgement has not been passed P (J'). 3. What is the probability for the cases for which judgement has not been passed and has no considerable number of evidences P(E'/J')? 4. What is the probability for the cases for which judgement were made on but did not account for the evidences filed against the accused. P (E'/J)? 5. What will be the total probability of evidence of presented cases in the courteven if they are considerable but were not considered and also not considerable but were considered. P(E)? 6. What will be the total probability of evidence not presented in all casesP(E')? 7. What will be the total probability of P(J'/E)? 8. What will be the total probability of P(J/E)? 9. What will be the total probability of P(J'/E')? 10. What will be the total probability of P(J/E')? Examiner 's Name: Dr Quist-Aphetsi Kester -.1/3 SECTION B An aircraft company has their flight data as shown in the table below, where a forward flight from A to B will take 4 miles and a return B to A will take 3 miles. A В D A 4 3 1 3 3 3 3 D 2 11. With the above information provided, draw a graph for the data provided. Indicate the weights on them. 12. Produce the adjacency matrix for your graph drawn 13. Find the shortest path in your graph and show the vertices and edges SECTION C An artificial intelligence system was design to forecast the financial trading market and predict change based on observed variables from the business environment. The variables to be observed are i. Population(A) ii. Poverty rate(B) iii. hflation (C) iv. Available resources(D) Theses variables can affect each other or impact upon one another. Below is a table of the variables with their effect on each other.
Jun 11, 2022
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