in this study a machine learning algorithm was applied in order to develop a predictive model for the changes in phytoplankton biomass (chlorophyll a) in the lower nakdong river, south korea. we used a “hybrid evolutionary algorithm (hea)” which generated model consists of three functions ‘if-thenelse’ on the basis of a 15-year, weekly monitored ecological database. we used the average ...

The Shifting Bottleneck (SB) heuristic is among the most successful approximation methods for solving the Job Shop problem. It is essentially a machine based decomposition procedure where a series of One Machine Sequencing Problems (OMSPs) are solved. However, such a procedure has been reported to be highly ineffective for the Flow Shop problems (Jain and Meeran 2002). In particular, we show th...

In this paper the resource-constrained flow shop (RCF) problem is addressed. A number of realistic extensions are incorporated, including non-serial precedence requirements, mixed flow shop situations, and the distribution of the human workforce among a number of pre-determined groups. The RCF is then solved by meta-heuristics, primarily of the evolutionary type. An extensive numerical investig...

Multiprocessor task scheduling is a generalized form of classical machine scheduling where a task is processed by more than one processor. It is a challenging problem encountered in wide range of applications and it is vastly studied in the scheduling literature (see for instance (Chan & Lee, 1999 and Drozdowski, 1996) for a comprehensive introduction on this topic). However, Drozdowski (1996) ...

in regions with deficient or no data, it is necessary to apply indirect methods to estimate the peak flow. regional flood analysis is the most accurate and reliable technique in such cases. one of the regional flood methods for flood analysis in arid and semi arid regions is hybrid technique, which was applied on data of khorasan razavi province watersheds to estimate the peak flow. hybrid meth...

Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...

Awareness of the level of river flow and its fluctuations at different times is one of the significant factor to achieve sustainable development for water resource issues. Therefore, the present study two hybrid models, Wavelet- Adaptive Neural Fuzzy Interference System (WANFIS) and Wavelet- Artificial Neural Network (WANN) are used for flow prediction of Gamasyab River (Nahavand, Hamedan, Iran...