Monthly Runoff Probabilistic Forecast Model Based on Similar Process Derivations

2015 ◽  
Vol 737 ◽  
pp. 710-714
Author(s):  
Cai Lin Lee ◽  
Dong Mei Wang
Keyword(s):  
Forecast Accuracy ◽  
Forecast Model ◽  
Probabilistic Forecast ◽  
Similar Process ◽  
Simulation Experiments ◽  
Model Combining ◽  
Forecast Result ◽  
Probabilistic Forecasts ◽  
Runoff Forecast ◽  
Monthly Runoff

In this paper, a runoff forecast model combining similar process derivation with probabilistic forecasts is proposed. Certain forecast result is computed by similar processes derivations, and on the basis of certain results, a confidence interval under given confidence coefficient is worked out by probabilistic forecast part. The model is simple in structure, easy in establishing and unnecessary to concern for predictor selections. Applying above model in simulation experiments, the results show the forecast model have excellent forecast accuracy and can be used in monthly runoff forecast effectively.

scholarly journals A Copula-Based Conditional Probabilistic Forecast Model for Wind Power Ramps

2019 ◽  
Vol 10 (4) ◽  
pp. 3870-3882 ◽  
Author(s):  
Mingjian Cui ◽  
Venkat Krishnan ◽  
Bri-Mathias Hodge ◽  
Jie Zhang
Keyword(s):  
Wind Power ◽  
Forecast Model ◽  
Probabilistic Forecast

scholarly journals Risk strategy analysis for an online rental problem of durable equipment with a transaction cost

2021 ◽  
Vol 15 ◽  
pp. 174830262110084
Author(s):  
Chunlin Xin ◽  
Jianwen Zhang ◽  
Ziping Wang
Keyword(s):  
Transaction Cost ◽  
Competitive Analysis ◽  
Competitive Ratio ◽  
Risk Tolerance ◽  
Probabilistic Forecast ◽  
Case Scenario ◽  
Strategy Analysis ◽  
Worst Case ◽  
Probabilistic Forecasts ◽  
Deterministic Strategy

This study introduces the second-hand market into the famous ski-rental model, presents an online rental problem of durable equipment with a transaction cost, and designs an optimal deterministic competitive strategy. The traditional competitive analysis is based on the worst-case scenario; hence, its results are too conservative. Even though investors want to manage and control their risks in reality, in some cases, they are willing to undertake higher risk to obtain greater benefits. Considering this situation, this study designs a risk strategy combining the decision makers’ risk tolerance with certain and probabilistic forecasts. Numerical analysis shows that the proposed risk strategy can improve the competitive ratio. This study introduces the idea of risk compensation into traditional competitive analysis and designs strategies for online rental of durable equipment based on forecast. The decision maker selects a strategy according to risk tolerance and forecast. If the forecast is correct, then a reward is obtained; otherwise, the risk is guaranteed to be within the decision maker’s risk tolerance. The optimal restricted ratio, that is, the competitive ratio of a risk strategy, is less than the optimal competitive ratio of a deterministic strategy. Therefore, the performance of the proposed risk strategy is better than a deterministic strategy. At the same time, the risk strategy based on the probabilistic forecast represents an extension of the strategy based on a certain forecast. In other words, the risk strategy based on a certain forecast is a special case of the risk strategy based on the probabilistic forecast.

Development of rainfall-runoff forecast model

2011 ◽  
Vol 8 (2) ◽  
Author(s):  
EO Oyebode ◽  
KO Adekalu ◽  
SA Akinboro
Keyword(s):  
Forecast Model ◽  
Rainfall Runoff ◽  
Runoff Forecast

A Method of Improved Support Vector Machine for Network Security Situation Forecasting

2011 ◽  
Vol 187 ◽  
pp. 291-296
Author(s):  
Yuan Cheng Li ◽  
Jing Tao Jing
Keyword(s):  
Network Security ◽  
Forecast Accuracy ◽  
Forecast Model ◽  
Selection Method ◽  
Support Vector ◽  
Swarm Optimization ◽  
Parameters Selection ◽  
Vector Machines ◽  
Good Forecast ◽  
Improved Support Vector Machine

Aiming at the problem that parameters of Support Vector Machines (SVM) are very difficult to confirm, this paper points out a parameter selection method for SVM based on Particle Swarm Optimization (PSO), which can make the SVM more scientific and reasonable in parameters selection; and thus enhance the forecast accuracy of the network security situation. The Simulation results show that the optimized SVR forecast model has good forecast accuracy for the network security situation, and present the future changing at a macro level, then help the network managers control network.

Prediction Model of Least Squares Support Vector Machine of Increased Memory Type Based on GA and Quadratic Renyi-Entropy

2011 ◽  
Vol 219-220 ◽  
pp. 754-761
Author(s):  
Guan Hua Zhao ◽  
Wen Wen Yan
Keyword(s):  
Support Vector Machine ◽  
Prediction Model ◽  
Least Squares ◽  
Financial Distress ◽  
Forecast Accuracy ◽  
Forecast Model ◽  
Renyi Entropy ◽  
Rényi Entropy ◽  
Support Vector ◽  
Memory Type

In order to improve the accuracy of financial achievement, this paper applies a new forecast model of the Increased memory type least squares support vector machine base on neighborhood rough set and quadratic Renyi-entropy on the basis of the traditional support vector machine prediction model. The paper also independently derives the entropy fit for the financial distress prediction which is in discrete sequence, as well as the expression of support vector machine kernel function. The experimental results show that the improved model is significantly superior to the traditional LS-SVM as well as the standard support vector machine prediction model, regardless of the forecast accuracy , training samples number.

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