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rainfall prediction through engineering analysis



Rainfall prediction using artificial neural networks
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ABSTRACT The spatial interpolation comparison 97 is concerned with predicting the daily rainfall at 367 locations based on the daily rainfall at nearby 100 locations in Switzerland. We propose a divide-and-conquer approach where the whole region is divided into four

Long-range monsoon rainfall prediction of 2005 for the districts and sub-division Kerala with artificial neural network
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Weather forecasting (especially rainfall) is one of the most important and challenging operational tasks carried out by meteorological services all over the world. Weather prediction is a complicated procedure that includes multiple specialized fields of expertise.

Application of multivariate ANFIS for daily rainfall prediction: influences of training data size
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Abstract This study investigates the use of multi variable Adaptive Neuro Fuzzy Inference System (ANFIS) in predicting daily rainfall using several surface weather parameters as predictors. The data used in this study comes from automatic weather station data

Long lead rainfall prediction using statistical downscaling and artificial neural network modeling
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Abstract. Long lead rainfall prediction is important in the management and operation of water resources and many models have been developed for this purpose. Each of the developed models has its special strengths and weaknesses that must be considered in

Prediction of seasonal rainfall in the north Nordeste of Brazil using eigenvectors of sea-surface temperature
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ABSTRACT Two statistical techniques, multiple linear regression and linear discriminant analysis, are compared for making hindcasts and real-time forecasts of north Nordeste (northeast Brazil) wet season rainfall using only information about sea-surface

An experiment of rainfall prediction over the Odra catchment by combining weather radar and a numerical weather model
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As more and more flood forecasting systems utilise quantitative precipitation forecast (QPF) in order to get a longer lead time, particularly for flash flood, attention has fallen upon the quality of QPF in such a model-train context. Weather radar and numerical weather

A study on short-term rainfall prediction by radar raingauge
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ABSTRACT A short-term rainfall prediction model using the echo-tracking method was applied to a number of rainfall cases to determine the accuracy of the model, and the accuracy of one-hour prediction proved to be practical. The echo-tracking method and the

Sindh summer (June-September) monsoon rainfall prediction
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Abstract: In this study effort has been made to examine the relationship of Sindh monsoon rainfall with some of very important global regional parameters. The Sindh Monsoon rainfall indices (SMRI) were examine with the monthly mean values of SST (SEA Surface

Association rule mining and classifier approach For quantitative spot rainfall prediction
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ABSTRACT Rainfall prediction is usually done for a region but spot quantitative precipitation forecast is required for individual township, harbours and stations with vital installation. A methodology using data mining technique has been tried for a coastal station, Cuddalore

A study on WRF radar data assimilation for hydrological rainfall prediction
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Abstract. Mesoscale numerical weather prediction (NWP) models are gaining more attention in providing highresolution rainfall forecasts at the catchment scale for realtime flood forecasting. The model accuracy is however negatively affected by the spin-up effect and

Rainfall-runoff models using artificial neural networks for ensemble streamflow prediction
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Abstract: Previous ensemble streamflow prediction (ESP) studies in Korea reported that modelling error significantly affects the accuracy of the ESP probabilistic winter and spring (ie dry season) forecasts, and thus suggested that improving the existing rainfall-runoff

Intra-seasonal rainfall characteristics and their importance to the seasonal predictionproblem
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ABSTRACT Daily station rainfall data in South Africa from 1936 to 1999 are combined into homogeneous rainfall regions using Ward's clustering method. Various rainfall characteristics are calculated for the summer season, defined as December to February.

Rainfall prediction using innovative grey model with the dynamic index
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ABSTRACT Taiwan's special climate and landforms are affected by summer typhoons, with 78% of its rainfall occurring during the summer and autumn months. The range and the severity of disasters has increased in recent years, thanks in part to climate change, which

Operational long-lead prediction of South African rainfall using canonical correlation analysis
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ABSTRACT A statistically based technique is used to study the variability and predictability of South African summer rainfall. The country is divided into homogeneous regions on the basis of the interannual rainfall variability. Canonical variates are then used to make 3-

Performance of artificial neural network and regression techniques for rainfall-runoffprediction
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Different types of methods have been used in runoff prediction involving conceptual and empirical models. Nevertheless, none of these methods can be considered as a single superior model. Owing to the complexity of the hydrological process, the accurate runoff is

Development of a fuzzy logic based rainfall prediction model
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ABSTRACT The present study investigates the ability of fuzzy rules/logic in modeling rainfall for South Western Nigeria. The developed Fuzzy Logic model is made up of two functional components; the knowledge base and the fuzzy reasoning or decisionmaking unit. Two

Seasonal summer rainfall prediction in Bermejo River Basin in Argentina
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Bermejo River Basin is located in the Chaco Plains in northern Argentina (Fig 1). The river has an extension of 1,450 km and the basin area covers 16,048 km2, comprising the north of Salta and the Formosa and Chaco provinces. Its principal tributary is San Francisco River

Modelling and prediction of rainfall using artificial neural network and ARIMA techniques
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ABSTRACT Climate and rainfall are highly non-linear and complicated phenomena, which require sophisticated computer modelling and simulation for accurate prediction. An artificial intelligence technology allows knowledge processing and can be used. as forecasting

Research Article Daily Rainfall-Runoff Prediction and Simulation Using ANN, ANFIS and Conceptual Hydrological MIKE11/NAM Models
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A bstract Rainfall-Runoff modelling is considered as one of the major hydrologic processes with a key role in predicting flood forecasting and water resources. Furthermore, in order to prevent damages caused by the flood and control and inhibit as well as management and

Bayesian prediction of rainfall records using the generalized exponential distribution
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SUMMARY The Los Angeles rainfall data are found to fit well to the two-parameter generalized exponential (GE) distribution. A Bayesian parametric approach is described and used to predict the behavior of further rainfall records. Importance sampling is used to

Rainfall-runoff prediction based on artificial neural network
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Abstract: The present study aims to utilize an Artificial Neural Network (ANN) to modeling the rainfall runoff relationship in a catchment area located in a semiarid region of Iran. The paper illustrates the applications of the feed forward back propagation for the rainfall forecasting

Rainfall prediction-measurement systems and rainfall design information for urban areas
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After intensive interaction with the Metropolitan Sanitary District of Greater Chicago (MSDGC) and awareness of the Chicago storm-sewer operational need, we concluded that a new form of rainfall prediction and monitoring system dedicated to MSDGC (and to other

Multiple site attenuation prediction models based on the rainfall structures (Meso-or synoptic scales) for advanced TLC or broadcasting systems
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ABSTRACT The paper presents a model for the statistical behaviour of those propagation parameters (such as the logarythm of the attenuation, lnA, or the one of the rain-intensity, lnR) which can be assumed to follow a multivariate gaussian distribution (an

Prediction of monsoon rainfall with a nested grid mesoscale limited area model
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Indian monsoon rainfall is dominated type disturbances, such as orographic rainfall along the west coast (Western Ghats) of India, and synoptically induced mesoscale convective systems during the passage of monsoon low pressure system. Our recent

The use of satellite derived rainfall estimates as inputs to flow prediction in the River Senegal
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ABSTRACT The research described in this paper investigates the accuracy obtainable in river flow forecasts when rainfall estimates based on Meteosat data are input to catchment models in place of raingauge data. Particularly where the raingauge network is sparse or

A Neuro-Fuzzy Approach for Daily Rainfall Prediction over the Central Region of Thailand
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Abstract:The methodology of neuro-fuzzy will be presented for the rain forecasting system over the central region of Thailand. The neuro-fuzzy approach was applied to create a classifier for rain prediction. The objective of this work is to demonstrate what relationship

Rainfall attenuation and rainfall rate measurements in Malaysia comparison with predictionmodels
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Abstract: Attenuation due to rain is a primary cause of communication impairment on satellite- earth paths, especially above 10GHz. Rainfall is a serious source of attenuation at such a frequency. This paper presents the characteristics of rain distribution in USM based on

Rainfall prediction for Chao Phraya river using neural networks with online data collection
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Abstract. Thailand's main profession is agriculture and rainfall is one of the major factors that play an important role for its economy. With the rainfall data sets of each station around Chao Phraya River during the period of recorded online every fifteen minutes

Empirical prediction of Indian summer monsoon rainfall with different lead periods based on global SST anomalies
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Summary The main objective of this study was to develop empirical models with different seasonal lead time periods for the long range prediction of seasonal (June to September) Indian summer monsoon rainfall (ISMR). For this purpose, 13 predictors having significant

Variable selection and prediction of rainfall from wsr-88 d radar using support vector regression.
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Abstract:-This research utilizes linear programming support vector regression to perform variable selection and rainfall estimation. Variables selected from applying linear programming support vector regression are used to perform rainfall prediction tasks using

Seasonal rainfall prediction in Kenya using empirical methods
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ABSTRACT Prediction schemes for forecasting of onset and cessation dates as well as seasonal amount of rainfall in the well known Kenyan long rains that extends from March to May (MAM) using Nairobi as the case study are proposed. In order to obtain onset and

Prediction of rainfall using support vector machine and relevance vector machine
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Abstract This article adopts Support Vector Machine (SVM) and Relevance Vector Machine (RVM) for prediction of rainfall in Vellore (India). SVM is firmly based on the theory of statistical learning theory. RVM is a probabilistic basis model. SVM and RVM use air

Structure and Parameter Determination of a Hydrologically Useful Rainfall Prediction Model
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ABSTRACT A physically based rainfall prediction model suitable for use with hydrologic catchment models has been developed in state space form. The structure defined by uniform height~ profiles for the updraft velocity and for the cloud layer~ average diameter

Comparison of short term rainfall forecasts for model based flow prediction in urban drainage systems
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Prediction of Rainfall Flow Time Series Using Autoregressive Models
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ABSTRACT Rain-fall flow data of a meteorological station like Vellore in Tamil Nadu have been used for mean monthly flow of rain-fall data using auto regressive approach. These approaches can be used for regenerating the future sequence preserving the inherited

Nonparametric prediction intervals for the future rainfall records
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SUMMARY Prediction of records plays an important role in the environmental applications, especially, prediction of rainfall extremes, highest water levels, sea surface, and air record temperatures. In this paper, based on the observed records drawn from a sequence

Digital computer solutions for flood hydrograph prediction from rainfall data
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ABSTRACT: A linear distributed-system model for flood hydrograph synthesization was applied to two characteristic test catchments (up to 700 sq. mi. in area) in central Europe, one of which was an Alpine watershed. The method uses very small elements, both in

rain fall prediction research recent 2014



Spatial rainfall prediction using optimal features selection approaches
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ABSTRACT Rainfall as a semi-random hydrological event is difficult to forecast due to some very complicated and unforeseen physical factors and their chaotic behavior. Artificial neural networks (ANNs), which perform a nonlinear mapping between inputs and outputs, have

ARMA (Autoregressive Moving Average) Model for Prediction of Rainfall in Regency of Semarang-Central Java-Republic of Indonesia
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Abstract Water is the main factor in determining the success of the activities of food crops, horticulture, and plantation. The main source of the water for agriculture and plantation comes from rainfall. This condition also occurs in regency of Semarang, Central Java,

Rainfall Prediction Using Data Mining techniques: A Survey
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Abstract: Data Mining is study of how to determine underlying patterns in the data. Data mining techniques like machine learning, alongside the conventional methods are deployed. Different Data mining techniques like GRNN, MLP, NNARX, CART, RBF,

Rainfall Prediction with TLBO Optimized ANN
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Rainfall prediction is very crucial for India as its economy is based on mainly agriculture. The parameters that are required to predict the rainfall are very complex in nature and also contain lots of uncertainties. Although various approaches have been earlier suggested

Prediction of Rainfall Using MLP and RBF Networks
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Prediction of rainfall for a region is of utmost importance for planning, design and management of irrigation and drainage systems. This can be achieved by different

Using subseasonal-to-seasonal (S2S) extreme rainfall forecasts for extended-range floodprediction in Australia
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Abstract. Meteorological and hydrological centres around the world are looking at ways to improve their capacity to be able to produce and deliver skilful and reliable forecasts of high- impact extreme rainfall and flooding events on a range of prediction timescales (eg sub-

Prediction of Moderate and Heavy Rainfall in New Zealand Using Data Assimilation and Ensemble
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This numerical weather prediction study investigates the effects of data assimilation and ensemble prediction on the forecast accuracy of moderate and heavy rainfall over New Zealand. In order to ascertain the optimal implementation of state-of-the-art 3Dvar and

A SURVEY ON RAINFALL PREDICTION USING DATAMINING
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Abstract India is an agricultural country and its economy is largely based upon crop productivity. For analyzing the crop productivity, rainfall prediction is require and necessary. Rainfall Prediction is the application of science and technology to foretell the state of the

A Comparison of Conceptual Rainfall-Runoff Modelling Structures and Approaches for Hydrologic Prediction in Ungauged Peatland Basins of the James Bay
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Abstract James Bay Lowland peatlands are environments with unique hydrologic characteristics that challenge some basic assumptions embedded within many hydrology models, including topographically-driven lateral flows and hydrologic connectivity of all

Short-Term Traffic Prediction Using Rainfall
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Abstract:We propose an approach to predict short-term travel time for expressways using rainfall data. The rainfall rate is quantitatively related to the travel time and is used to perform the prediction. The proposed approach is experimented on real data collected in

Time-prediction of the onset of rainfall-induced landslides based on the monitoring of surface displacement and groundwater level
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Abstract Analysis of monitoring data on the deformation in sandy model slope under artificial rainfall was conducted in this study. The analysis revealed that the relationship between the surface displacement and the groundwater level in the slope was modified as hyperbolic

Interpretable Fuzzy Systems for Monthly Rainfall Spatial Interpolation and Time SeriesPrediction
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In the first part, this thesis proposes a methodology to analyze and establish interpretable fuzzy models for monthly rainfall spatial interpolation using global and local methods. In the global method, the proposed methodology begins with clustering analysis to determine

Carrier Class Availability Prediction for Hybrid FSO/RF System in Heavy Rainfall Regions Based on ITU-R Models
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Abstract:Availability is considered as the main parameter of evaluating a Hybrid FSO/RF link quality. An accurate carrier class availability prediction of Hybrid FSO/RF is needed. In tropical regions, among different weather influences, rain plays a major role. Precipitation


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