In this work, we introduce a new modeling and inferential tool for dynamical processing of time series. The approach is called recurrent dictionary learning (RDL). proposed model reads as linear Gaussian Markovian state-space involving two operators, the state evolution observation matrices, that assumed to be unknown. These unknown operators (that can seen interpreted dictionaries) sequence hi...

This paper examines the utility of high-resolution airborne RGB orthophotos and LiDAR data for mapping residential land uses within the spatial limits of suburb of Athens, Greece. Modern remote sensors deliver ample information from the AOI (area of interest) for the estimation of 2D indicators or with the inclusion of elevation data 3D indicators for the classification of urban land. In this r...

The nature of electric force and unsettling influences happened in power signal has gotten a significant issue between the providers & clients. For enhancing quality constant checking is required that being conveyed at client's destinations. Thusly, recognition “POWER QUALITY” aggravations, appropriate characterization D profoundly attractive. location appropriation frameworks are errands f...

The use of the artificial neural networks in economics and business goes back to 1950s, while the major bulk of the applications have been developed in more recent years. Reviewing this literature indicates that the field of business benefits from the neural networks in a wide spectrum from prediction to classification, as most of the applications in economics primarily focus on the predictive ...

Dengue fever (DF) is an acute febrile viral disease frequently presented with headache, bone or joint and muscular pains, and rash. A significant percentage of DF patients develop a more severe form of disease, known as dengue haemorrhagic fever (DHF). DHF is the complication of DF. The main pathophysiology of DHF is the development of plasma leakage from the capillary, resulting in haemoconcen...

in this paper, the application of neural networks for simulation and optimization of the cogeneration systems has been presented. cgam problem, a benchmark in cogeneration systems, is chosen as a casestudy. thermodynamic model includes precise modeling of the whole plant. for simulation of the steadysate behavior, the static neural network is applied. then using dynamic neural network, plant is...

During the last few years, multi-objective optimization processes have become one of main challenges for energy efficiency in buildings. In this work, a new efficient method, based on Building Performance Optimization (BPO) technique, has been developed to improve indoor thermal comfort and performance residential buildings, i.e. Moroccan ground floor + first (GFFF) house located Marrakech regi...

During the recent decades, neural network models have been focused upon by researchers due to their more real performance and on this basis, different types of these models have been used in forecasting. Now, there is a question that which kind of these models has more explanatory power in forecasting the future processes of the stock. In line with this, the present paper made a comparison betw...