Planning Production Capacity Using Time Series Forecasting Method and Linier Programming

Time Series Forecasting Using Massively Parallel Genetic Programming

In this paper we propose a massively parallel GP model in hardware as an efficient, flexible and scaleable machine learning system. This fine-grained diffusion architecture consists of a large amount of independent processing nodes that evolve a large number of small, overlapping subpopulations. Every node has an embedded CPU that executes a linear machine code GP representation at a rate of up...

Genetic Programming and Boosting Technique to Improve Time Series Forecasting

Forecasting economic time series using unobserved components time series models

A preliminary version, please do not quote

Time Variant Fuzzy Time Series Approach for Forecasting Using Particle Swarm Optimization

  Fuzzy time series have been developed during the last decade to improve the forecast accuracy. Many algorithms have been applied in this approach of forecasting such as high order time invariant fuzzy time series. In this paper, we present a hybrid algorithm to deal with the forecasting problem based on time variant fuzzy time series and particle swarm optimization algorithm, as a highly effi...

Dynamic time-series forecasting using local approximation

Pattern recognition techniques for time-series forecasting are beginning to be realised as an important tool for predicting chaotic behaviour of dynamic systems. In this paper we develop the concept of a Pattern Modelling and Recognition System which is used for predicting future behaviour of time-series using local approximation. In this paper we compare this forecasting tool with neural netwo...