Prediction system using fuzzy logic and ANN
Budget: $10 – $30 CAD
1) At least a fuzzy logic model and a neural network system have to be used for programming, and two inputs and single output should be the minimum variables.
2) Programming can be undertaken in a MATLAB environment or by C language or Python. The fundamental functionalities in NNs and training can be either programmed by yourself or using MATLAB toolboxes.
3) Fuzzy logic, ANFIS, LSE, gradient descent and other AI algorithms can be used for the architecture and parameter optimization or NN training.
4) Some models different from your methods can be used for performance comparison in terms of structure and parameter training.
5) It is recommended to use an error threshold of 10-4 and 200 training epochs.
2) Programming can be undertaken in a MATLAB environment or by C language or Python. The fundamental functionalities in NNs and training can be either programmed by yourself or using MATLAB toolboxes.
3) Fuzzy logic, ANFIS, LSE, gradient descent and other AI algorithms can be used for the architecture and parameter optimization or NN training.
4) Some models different from your methods can be used for performance comparison in terms of structure and parameter training.
5) It is recommended to use an error threshold of 10-4 and 200 training epochs.