Jon B. Weissman Division of Computer Science University of Texas at San Antonio San Antonio, TX 78249 USA (210-458-5689 voice, 210-458-4437 fax) ([email protected]) Abstract Obtaining efficient execution of parallel programs in workstation networks is a difficult problem for the user. Unlike dedicated parallel computer resources, network resources are shared, heterogeneous, vary in availability, ...

This work proposes the Cultural Greedy Ant (CGrAnt) protocol to solve the problem of data delivery in opportunistic and intermittently connected networks referred to as Delay Tolerant Networks (DTNs). CGrAnt is a hybrid Swarm Intelligence-based forwarding protocol designed to address the dynamic and complex environment of DTNs. CGrAnt is based on: (1) Cultural Algorithms (CA) and Ant Colony Opt...

In recent years, many studies have been done on forecasting fuzzy time series. First-order fuzzy time series forecasting methods with first-order lagged variables and high-order fuzzy time series forecasting methods with consecutive lagged variables constitute the considerable part of these studies. However, these methods are not effective in forecasting fuzzy time series which contain seasonal...

in the regulated nakdong river, algal proliferations are annually observed in some seasons, with cyanobacteria (microcystis aeruginosa) appearing in summer and diatom blooms (stephanodiscus hantzschii) in winter. this study aims to develop two ecological models forecasting future chlorophyll a at two time-steps (one-week and one-year forecasts), using recurrent neural networks tuned by genetic...

In this paper, we propose a new residual analysis method using Fourier series transform into fuzzy time series model for improving the forecasting performance. This hybrid model takes advantage of the high predictable power of fuzzy time series model and Fourier series transform to fit the estimated residuals into frequency spectra, select the low-frequency terms, filter out high-frequency term...

Sales forecasting is an essential component of business management, providing insight into future sales and revenue. It critical for effective inventory cash flow, growth planning. While many retailers rely on simple Excel functions or subjective guesses from the industry increasingly turning to machine learning techniques develop more accurate reliable prediction models. Among these techniques...