abstract recent interest in describing the spatial distribution patterns of weeds through using interpolation methods has increased to estimate weed seedling density from spatially refferenced data and evaluation of applicable to site-specific weed management. in this research, a multi layer perceptron neural network (mlpnn) model was developed to predict the spatial distribution of h. glaucum ...

This research presents the battery discharge rate models for the energy consumption of mobile phone batteries based on machine learning by taking into account three usage patterns of the phone: the standby state, video playing, and web browsing. We present the experimental design methodology for collecting data, preprocessing, model construction, and parameter selections. The data is collected ...

this study aims at comparing the performance of logistic regression, maximum entropy, and multilayer perceptron techniques in preparing the predictive habitat distribution map of amygdalus scoparia in rangelands of qom province. for this purpose, vegetation sampling was done using random systematic methods after identifying pure habitats of this species. for soil sampling, eight profiles were e...

The artificial neural networks, the learning algorithms and mathematical models mimicking the information processing ability of human brain can be used non-linear and complex data. The aim of this study was to predict the breeding values for milk production trait in Iranian Holstein cows applying artificial neural networks. Data on 35167 Iranian Holstein cows recorded between 1998 to 2009 were ...

The multilayer perceptron (MLP) is a well established neural network model for supervised learning problems. Furthermore, it is well known that its performance for a given problem depends crucially on appropriately selecting the MLP architecture, which is typically achieved using cross-validation. In this work, we propose an incremental Bayesian methodology to address the important problem of a...

Feature projection by non-linear discriminant analysis (NLDA) can substantially increase classification performance. In automatic speech recognition (ASR) the projection provided by the pre-squashed outputs from a one hidden layer multi-layer perceptron (MLP) trained to recognise speech subunits (phonemes) has previously been shown to significantly increase ASR performance. An analogous approac...

estimating of forest equipment productivity is an important aspect of managing cost in forestry, which leads to reduction of operations expenses. in other words, high capital cost in forest harvesting, is a good reason to argue forest engineering research and time modeling. this paper applied one of the artificial intelligence subsets, which are called artificial neural networks (anns), to pred...