M-Factor High Order Fuzzy Time Series Forecasting for Road Accident Data

A Two Phase Algorithm for Fuzzy Time Series Forecasting using Genetic Algorithm and Particle Swarm Optimization Techniques

“…In the first phase we have applied GA to optimize weights w1, w2, w3 used in formula (Jilani, Burney [15]). …”

“…Step 6: For two-factor k-order fuzzy logical relationship in Table -5, the forecasted value is calculated using (Jilani, Burney [14]):…”

“…Step 6: For m-factor kth order fuzzy logical relationship, the forecasted value of day j based on history of third order is calculated as follows (Jilani and Burney [14]), Step 7: Compare MSE value of current particle with local best particle's MSE value and set current particle as local best in case current MSE is lower than local best MSE value.…”

“…Song and Chissom [1,2] used the concept of FTS and forecasted number of enrollments of the University of Alabama. Many other researchers proposed their models for enrollments forecasting of the University of Alabama ( [3], [4], [5], [6], [7], [8], [9], [10] and [11]), temperature prediction [12,13] and car road accidents [14,15] using fuzzy time series. Huarng [7] presented heuristic based model for fuzzy time series forecasting.…”

“…Huarng [7] presented heuristic based model for fuzzy time series forecasting. Jilani and Burney [14] presented M-factor high order fuzzy time series forecasting model for car road accident data. Jilani and Burney [16] presented new heuristic based approach for frequency density based partitioning for fuzzy time series forecasting of stock market.…”