Small Support Vector Machine Example for Prediction
A compact MATLAB-based Support Vector Machine implementation for predictive modeling using Least Squares (LS) optimization
Algorithm Implementation for Predicting Circular Motion Using Kalman Filter
Implementation of Circular Motion Prediction Algorithm with Kalman Filter Approach
Neural Network-Based Traffic Flow Prediction in MATLAB
MATLAB Neural Network Traffic Flow Prediction with Optimized Source Code
MATLAB Time Series Modeling, Prediction, and Implementation with Program Code
1) Generate a .wav file by encoding your contact phone number using DTMF (Dual-Tone Multi-Frequency) signaling with MATLAB. Implementation typically involves using the `audiowrite` function and generating dual-frequency sine waves for each digit. 2) Decode the generated DTMF file to extract the encoded telephone number. This requires implementing a Goertzel algorithm or FFT-based frequency detection to identify the characteristic tone pairs in the audio signal.
Support Vector Machine Regression for Concrete Compressive Strength Prediction
Support Vector Machine (SVM) is a generalized linear classifier that performs binary classification using supervised learning, with its decision boundary defined by the maximum-margin hyperplane derived from training samples. This implementation applies SVM regression to predict concrete compressive strength, featuring verified functionality and practical code implementation.
Support Vector Regression (SVR) Implementation Guide
A practical application of Support Vector Regression machine! Perfect for beginners learning prediction modeling with clear code examples and algorithm explanations.
Grey Neural Network for Order Demand Forecasting
Implementing Grey Neural Network Models to Predict Order Demand with Code-Based Approaches
Implementation of Cognitive Radio Detection and Prediction Using BP Neural Network
Using BP neural networks for cognitive radio spectrum detection and prediction, achieving efficient spectrum allocation through machine learning algorithms with backpropagation weight optimization
Least Squares Support Vector Machine (LS-SVM)
Least Squares Support Vector Machine for multivariate nonlinear regression analysis, nonlinear fitting and prediction with enhanced computational efficiency and simplified optimization.
MATLAB Implementation of Chaotic Neural Networks
This MATLAB program implements a chaotic neural network that can be used for prediction and modeling tasks using chaotic neural network algorithms.