alzheimer's disease (ad) is the most common form of neurodegenerative disorders. memory loss in an alert person and impairment in the function of language, attention, perception, judgment or problem solving can occur in patients with ad. however, there are some medications in order to delay the debilitating aspects of the disease; but unfortunately, scientists could not found approaches to...

clustering is the process of dividing a set of input data into a number of subgroups. the members of each subgroup are similar to each other but different from members of other subgroups. the genetic algorithm has enjoyed many applications in clustering data. one of these applications is the clustering of images. the problem with the earlier methods used in clustering images was in selecting in...

this paper presents a hybrid approach to developing a short-term traffic flow prediction model. in thisapproach a primary model is synthesized based on neural networks and then the model structure is optimized throughgenetic algorithm. the proposed approach is applied to a rural highway, ghazvin-rasht road in iran. the obtainedresults are acceptable and indicate that the proposed approach can i...

a total of 2000 records of egg quality of 746 birds and body weight data from 17th generation of fars native fowl breeding station were used to estimate the genetic parameters of egg quality and body weight traits. six univariate animal models with different random effects were fitted for each trait. a model with direct additive genetic and maternal permanent environmental effects was the most ...

in this research, 6517 records, collected by khojir sheep breeding station (tehran, iran), during 1991 to 2011 were used to estimate genetic parameters of lamb survival in zandi sheep. genetic parameters were estimated using 16 different models of animal model, sire and threshold models using reml procedures. the aic criterion was used to evaluate the models. the effects in the most suitable an...

this study emphasized the ability of genetic algorithm and cellular automate to simulate urban land use changes by integrating adaptive model. the most important part of modeling is to define transition rules.  in this research, a cellular automata model in dinamica ego software was used coupled with genetic algorithm. according to disability of the software for manipulating large number of var...

the forecasting of hydrological variables, such as streamflow, plays an important role in water resource planning and management. recently, the development of stochastic models is regarded as a major step for this purpose. streamflow forecasting using the arima model can be conducted when unknown parameters are estimated correctly because parameter estimation is one of the crucial steps in mode...

a novel approach to determine optimal sampling locations under parameter uncertainty in a water distribution system (wds) for the purpose of its hydraulic model calibration is presented. the problem is formulated as a multi-objective optimisation problem under calibration parameter uncertainty. the objectives are to maximise the calibrated model accuracy and to minimise the number of sampling d...