[PDF] Top 20 Forecasting Grain Supply and Demand with Support Vector Regression
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Forecasting Grain Supply and Demand with Support Vector Regression
... the demand and supply of ...of grain demand and pointed out there will have shortage between demand and supply in ...of grain demand and supply using the ... See full document
5
Particle swarm optimized–support vector regression hybrid model for daily horizon electricity demand forecasting using climate dataset
... electricity demand ( G) obtained from the Australian Energy Market Operator ...a support vector regression (SVR) model was applied in this study for the G forecasting, where the model’s ... See full document
5
Water Demand Prediction using Artificial Neural Networks and Support Vector Regression
... water demand and the study is restricted to South Africa’s Gauteng ...the demand of water is much higher than the rate at which the water is being supplied ...water demand exceeding the water ... See full document
8
Long Term Load Forecasting and Recommendations for China Based on Support Vector Regression
... on support vector machines (SVMs), i.e. support vector regression (SVR), has been proposed for load forecasting because of the structural risk minimization (SRM) principle to ... See full document
6
Seasonal Based Electricity Demand Forecasting Using Time Series Analysis
... on forecasting model which includes support vector regression (SVR) model, chaotic immune algorithm and seasonal adjustment mechanism to forecast monthly electric ...to forecasting for ... See full document
10
Short Term Load Forecasting Using A Hybrid Model Based On Support Vector Regression
... This paper proposed a hybrid method based on SVR and KH algorithm to predict the load data with more accuracy. The proposed method uses the KH algorithm to adjust the kernel function (σ) and the optimal hyper plane ... See full document
7
Sales Forecasting using Linear Regression and Support Vector Machine
... intelligent forecasting methods can play in the world of Sales ...in demand over time, can bring relief and are a must to maintain control over the supply ...sophisticated forecasting ... See full document
7
Drought forecasting in eastern Australia using multivariate adaptive regression spline, least square support vector machine and M5Tree model
... Drought is an insidious natural hazard that occurs as a normal, yet a recurrent feature in an arid, semi-arid, desert or rain-forested region (Wilhite et al., 2000a; Keyantash and Dracup, 2002; Vicente-Serrano, 2016). ... See full document
68
Prediction of Tanzanian Energy Demand using Support Vector Machine for Regression (SVR)
... energy demand to be of great interest to ...energy demand is expected to grow [1] as new investments floods in due to economic sectors expansions and liberalization especially in gas, minerals and ...adopts ... See full document
6
Hybridizing GMDH and least squares SVM support vector machine for forecasting tourism demand
... the support vector machine (SVM) method, which was first suggested by Vapnik in 1995 [1], has recently been used in various applications such as in data mining, tourism, classification, regression ... See full document
6
Co regularised support vector regression
... The idea for mutual influence of multiple predictors appeared in the paper of Blum and Mitchell [2] on classification with co-training. Wang et al. [14] combined the tech- nique of co-training with SVR with a technique ... See full document
16
Three layer wavelet based modeling for river flow
... or forecasting of the magnitude of hydrological variables like precipitation, stream flow and groundwater levels using historical ...water supply or ... See full document
50
An Improved Neural Approaches for Forecasting Demand in Supply Chain Management
... Demand forecasting plays a pivotal role for supply chain ...Several forecasting techniques have been developed, each one has its particular benefits and limitations compared to other ... See full document
8
The efficacy of using data mining techniques in predicting academic performance of architecture students.
... Research into student’s academic performance at universities has a long history. In one of the first published studies on this topic, Wagner and Strabel (1935) found that prior academic achievement at high school, ... See full document
59
Time Series Forecasting Using Wavelet Least Squares Support Vector Machines and Wavelet Regression Models for Monthly Stream Flow Data
... The selection of appropriate input data sets is an impor- tant consideration in the LSSVM modeling. In the train- ing and testing of LSSVM model, the same input struc- tures of the data set (M1 - M6) were used. In order ... See full document
12
Parameters Optimization Using Genetic Algorithms in Support Vector Regression for Sales Volume Forecasting
... An artificial neural network (ANN) is a new contender in forecasting sophisticated trend and seasonal data. Artificial intelligent models have more flexibility and can be used to estimate the non-linear ... See full document
7
Analysis of the Influence Factors of Grain Supply Demand Gap in China
... the grain supply and demand gap’s current situation in China, this paper establishes an indicator system for the influence factors of grain supply and demand ...main grain ... See full document
9
Large-scale Linear Support Vector Regression
... Support vector regression (SVR) is a widely used regression technique (Vapnik, ...from support vector classification (SVC) by Boser et ... See full document
26
Application of the discrete separation theorem to auctions
... For each i ∈ N, Gul and Stacchetti (2000) called the above minimum value the requirement function and interpreted it as follows: “the minimal number of objects in A that she would need to construct any of her optimal ... See full document
15
The Application of Support Vector Machine in Load Forecasting
... combination forecasting method was proposed by Bates and Granger[9], its essence is to utilize the single model of information and obtain the combination forecasting model through the appropriate weighted ... See full document
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