Prediction of the next-crossing cell is an important issue for mobility and connection management in wireless radio networks. In this paper, we propose a new approach to modeling inter-cell user mobility, and develop an optimum self-learning estimator for trajectory tracking and next-crossing cell prediction. The dynamic states of movement, in terms of speed and position, are obtained by modeli...

statistical methods, and especially machine learning, have been increasingly used in nanofluid modeling. this paper presents some of the interesting and applicable methods for thermal conductivity prediction and compares them with each other according to results and errors that are defined. the thermal conductivity of nanofluids increases with the volume fraction and temperature. machine learni...

In this paper we present a new lossless image compression algorithm. To achieve the high compression speed we use a linear prediction, modified Golomb–Rice code family, and a very fast prediction error modeling method. We compare the algorithm experimentally with others for medical and natural continuous tone grayscale images of depths of up to 16 bits. Its results are especially good for big i...

a quanitative structure property relationship was proposed to calculate the binary interaction terms of the jouyban-acree model using solubility parameter, boiling point, vapour pressure and density of solvents. the applicability of the proposed method for reproducing solubility data of anthracene in binary solvents has been evaluated using 116 solubility data sets collected from the literature...

This paper focuses on the analysis of prediction of wind speed in the wind farms. The performance of modeling can be analyzed by using the real time data with different heights of the wind mill. Artificial Neural Network is used here to develop models for predicting wind speed in wind farms. The models are mainly based on back propagation neural network and radial basis function neural network....

This paper is an attempt to assess the potential and usefulness of ANN based modeling for evaporation prediction from a reservoir, where in classical and empirical equations failed to predict the evaporation accurately. The meteorological data set of daily pan evaporation, temperature, solar radiation, relative humidity, wind speed is used in this study. The performance of feed forward back pro...

In the recent years there is a lot of research happening to predict wind speed with several mathematical methods and biologically inspired computing techniques to reduce the prediction error. A new strategy in wind speed prediction is proposed in this paper and the Adaptive Neuro-Fuzzy Inference System (ANFIS) is applied to forecast the speed of wind. ANFIS can forecast very well of the next va...

As the graphical and mathematical representation of relationships among traffic flow, speed, and density, the fundamental diagram has been the foundation of traffic flow theory and transportation engineering. Underlying the fundamental diagram is the speed-density relationship which was originally documented in Greenshields’ seminal work and followed by a variety of equilibrium models over the ...