`Only for the MLP do we include the hourly weather data as part of the input space, resulting in 25 features. And for the ResNet model, we one-hot encode day of the week and month into our input space, resulting in 41 initial input features. MULTILAYER PERCEPTRON (MLP) Our baseline of comparison is a basic MLP that consists of three fully connected layers, containing a hidden layer with 24 neur...

The combined use of multi layer perceptron (MLP) and perceptual linear prediction (PLP) features has been reported to improve the performance of automatic speech recognition systems for many different languages and domains. However, MLP features have not yet been used on unsupervised acoustic model training. This approach is introduced in this paper with encouraging results. In addition, unsupe...

abstract process of evapotranspiration (eto) is a major component of the hydrologic cycle that its accurate estimation plays an important role to achieve sustainable development in water balance, irrigation system design and planning and management of water resources. being a function of different metrological parameters and their interactions, evapotranspiration is a complex, nonlinear phenome...

Link admission control (LAC) in broadband ATM networks is based on evaluation of expected traffic performance. The traditional LAC approach relies on approximate analytical performance models, and can lead to an over controlled network. This paper presents a hybrid LAC scheme which uses a multi layer perceptron (MLP) to refine the performance estimate of a traditional analytical approximation. ...

The paper describes an artificial neural network (ANN) model to predict the height of destressed zone (HDZ) which is taken as equivalent to the combined height of caved and fractured zones above the mined panel in longwall mining. For this, the suitable datasets have been collected from the literatures and prepared for modeling. The data were used to construct a multilayer perceptron (MLP) netw...

The purpose of this paper is twofold. Firstly, to assess the merit of estimating probability density functions rather than level or classification estimations on a oneday-ahead forecasting task of the EUR/USD time series. This is implemented using a Gaussian mixture model neural network, benchmarking the results against standard forecasting models, namely a naïve model, a moving average converg...

in this paper, a state-of-the-art neuron mathematical model of neural tensor network (ntn) is proposed to rdf knowledge base completion problem. one of the difficulties with the parameter of the network is that representation of its neuron mathematical model is not possible. for this reason, a new representation of this network is suggested that solves this difficulty. in the representation, th...

To estimate the Cation Exchange Capacity (CEC), indirect manner used of Pedotransfer Functions (PTFs). CEC is one of the important soil fertility factors, and not measured directly because it is costly and time consuming. Thus, used from regression equations between easily and non-easily soil properties. The purpose of this research, is develop the PTFs for CEC, with use of easily available soi...

Since artificial neural networks (ANNs) can approximate any function, they have been applied in many fields including hydrology. In hydrology, there are important issues such as flood estimation and predicting rainfall-runoff in a certain area. In this presentation, we briefly introduce a popular feed-forward neural network model, so called “multi-layer perceptron (MLP)”, and review its applica...

Dr. David Shahian Lahey Clinic Burlington, MA 01805 Experiments demonstrated that sigmoid multilayer perceptron (MLP) networks provide slightly better risk prediction than conventional logistic regression when used to predict the risk of death, stroke, and renal failure on 1257 patients who underwent coronary artery bypass operations at the Lahey Clinic. MLP networks with no hidden layer and ne...