scholarly journals Forecasting of Rainfall in Central Java using Hybrid GSTAR-NN-PSO Model

2019 ◽  
Vol 125 ◽  
pp. 23015
Author(s):  
Hasbi Yasin ◽  
Budi Warsito ◽  
Rukun Santoso ◽  
Arief Rachman Hakim
Keyword(s):  
Neural Network ◽  
Flood Control ◽  
Forecast Accuracy ◽  
Space Time ◽  
Rainfall Data ◽  
Time Data ◽  
Feed Forward Neural Network ◽  
Time Model ◽  
Central Java ◽  
Space Time Model

Forecasting of rainfall trends is essential for several fields, such as airline and ship management, flood control and agriculture. The rainfall data were recorded several time simultaneously at a number of locations and called the space-time data. Generalized Space Time Autoregressive (GSTAR) model is one of space-time models used to modeling and forecasting the rainfall. The aim of this research is to propose the nonlinear space-time model based on hybrid of GSTAR, Feed Forward Neural Network (FFNN) and Particle Swarm Optimization (PSO) and it called GSTAR-NN-PSO. In this model, input variable of the FFNN was obtained from the GSTAR model. Then use PSO to initialize the weight parameter in the FFNN model. This model is applied for forecasting monthly rainfall data in Jepara, Kudus, Pati and Grobogan, Central Java, Indonesia. The results show that the proposed model gives more accurate forecast than the linear space-time model, i.e. GSTAR and GSTAR-PSO. Moreover, further research about space-time models based on GSTAR and Neural Network is needed to improving the forecast accuracy especially the weight matrix in the GSTAR model.

scholarly journals Space-Time Model to Predict The Evolution of the Regional Subsidence in The Lacustrine Zone of Mexico City

2021 ◽  
Author(s):  
Maria Clara Madrigal-Madrigal ◽  
Eduardo Botero-Jaramillo ◽  
Carlos Díaz-Ávalos
Keyword(s):  
Mexico City ◽  
Ground Surface ◽  
Temporal Correlation ◽  
Space Time ◽  
Time Data ◽  
Time Model ◽  
Time Period ◽  
The One ◽  
Available Information ◽  
Space Time Model

Abstract In several scientific and engineering disciplines, models have been used to understand the behavior of dynamic processes that evolve in space and in time by providing a probabilistic framework to analyzing the available information. The geostatistical tools used to analyze space-time data are based on established statistical methods, where time is considered as an additional dimension. These models have become very useful in fields such as meteorology, hydrology, ecology, geosciences, and environmental sciences, among others. Subsidence generated by the intense extraction of groundwater in a region is a dynamic phenomenon that manifests itself through the sinking of the ground surface, leading to significant settling in buildings and public utilities as well as cracks in roads. Since the regional subsidence of Mexico City is one of the most representative cases of this type in the world, in this work a model with a full grid space-time layout (STF) is used to analyze and predict the evolution of this phenomenon in the city, taking into account a monitoring system composed of 1931 surface benchmarks. Results show that the separable variogram model was the one that best represented the spatial and temporal correlation of the phenomenon in the area of study. In addition, the differences between the registered ground elevation made in 2016 and those estimated by the space-time model for the same year, were less than 1.00 m. This implies that in general accurate ground elevation values and subsidence rates can be obtained from the proposed space-time model during the time period 2010-2030 for the lacustrine zone of Mexico City.

Tail asymptotics of an infinitely divisible space-time model with convolution equivalent Lévy measure

2021 ◽  
Vol 58 (1) ◽  
pp. 42-67 ◽  
Author(s):  
Mads Stehr ◽  
Anders Rønn-Nielsen
Keyword(s):  
Space Time ◽  
Time Interval ◽  
Lévy Measure ◽  
Infinitely Divisible ◽  
Time Model ◽  
Spatial Object ◽  
Tail Behaviour ◽  
Fixed Radius ◽  
The Right ◽  
Space Time Model

AbstractWe consider a space-time random field on ${{\mathbb{R}^d} \times {\mathbb{R}}}$ given as an integral of a kernel function with respect to a Lévy basis with a convolution equivalent Lévy measure. The field obeys causality in time and is thereby not continuous along the time axis. For a large class of such random fields we study the tail behaviour of certain functionals of the field. It turns out that the tail is asymptotically equivalent to the right tail of the underlying Lévy measure. Particular examples are the asymptotic probability that there is a time point and a rotation of a spatial object with fixed radius, in which the field exceeds the level x, and that there is a time interval and a rotation of a spatial object with fixed radius, in which the average of the field exceeds the level x.

A Deterministic Sea-Clutter Space–Time Model Based on Physical Sea Surface

2016 ◽  
Vol 54 (11) ◽  
pp. 6659-6673 ◽  
Author(s):  
Zhihui Xin ◽  
Guisheng Liao ◽  
Zhiwei Yang ◽  
Yuhong Zhang ◽  
Hongxing Dang
Keyword(s):  
Space Time ◽  
Sea Surface ◽  
Sea Clutter ◽  
Time Model ◽  
Model Based ◽  
Space Time Model

Beyond Gödel’s Time

2018 ◽  
Vol 4 (1) ◽  
Author(s):  
Peter Riggs
Keyword(s):  
Theoretical Model ◽  
Space Time ◽  
Time Model ◽  
Space Time Model

The Gödel space-time model displays an intrinsic rotation of matter, which is responsible for some fascinating characteristics. It is a theoretical model of a possible, though not the actual, universe.

Theory of the Stationary Self-Consistent Universe

2021 ◽  
Author(s):  
Alexander Shamailovich Avshalumov
Keyword(s):  
Quantum Physics ◽  
Space Time ◽  
Theoretical Physics ◽  
Time Model ◽  
Zero Curvature ◽  
Modern Cosmology ◽  
Simultaneous Existence ◽  
Three Space ◽  
Space Time Model ◽  
The Universe

Since the creation of GR and subsequent works in cosmology, the question of the curvature of space in the Universe is considered one of the most important and debated to this day. This is evident, because the curvature of space depends whether the Universe expands, contracts or is static. These discussions allowed the author to propose a paradoxical idea: simultaneous existence in the Universe of three interconnected space-times (positive, negative and zero curvature) and on this basis, to develop a theory in which each space-time plays its own role and develops in a strict accordance with its sign of curvature. The three space-time model of the structure of the Universe, proposed by the author, allows to solve many fundamental problems of modern cosmology and theoretical physics and creates the basis for building a unified physical theory (including one that unites GR and quantum physics).

scholarly journals A Space-Time Model with Application to Annual Temperature Anomalies;

2003 ◽  
Vol 10 (1) ◽  
pp. 19-30
Author(s):  
Eui-Kyoo Lee ◽  
Myung-Sang Moon ◽  
Richard F. Gunst
Keyword(s):  
Space Time ◽  
Time Model ◽  
Temperature Anomalies ◽  
Space Time Model

INFLATIONARY SCENARIO IN BRANS–DICKE THEORY FOR BIANCHI VI0 SPACE–TIME MODEL

2003 ◽  
Vol 12 (01) ◽  
pp. 129-143 ◽  
Author(s):  
SUBENOY CHAKRABORTY ◽  
ARABINDA GHOSH
Keyword(s):  
Equation Of State ◽  
Perfect Fluid ◽  
Analytical Solutions ◽  
Fluid Model ◽  
Space Time ◽  
Time Model ◽  
Exact Analytical Solutions ◽  
Exponential Expansion ◽  
Barotropic Equation ◽  
Space Time Model

We have investigated perfect fluid model in Brans–Dicke theory for Bianchi VI 0 space–time and have obtained exact analytical solutions considering barotropic equation of state. These solutions have been analyzed for different values of the parameters involved and some of them have shown a period of exponential expansion.

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