Clustering and Support Vector Regression for Water Demand Forecasting and Anomaly Detection

Monthly rainfall Forecasting using genetic programming and support vector machine

Rainfall and runoff estimation play a fundamental and effective role in the management and proper operation of the watershed, dams and reservoirs management, minimizing the damage caused by floods and droughts, and water resources management. The optimal performance of intelligent models has increased their use to predict various hydrological phenomena. Therefore, in this study, two intelligent...

Tehran Stock Price Modeling and Forecasting Using Support Vector Regression (SVR) and Its Comparison with the Classic Model ARIMA

Anomaly Detection Using SVM as Classifier and Decision Tree for Optimizing Feature Vectors

Abstract- With the advancement and development of computer network technologies, the way for intruders has become smoother; therefore, to detect threats and attacks, the importance of intrusion detection systems (IDS) as one of the key elements of security is increasing. One of the challenges of intrusion detection systems is managing of the large amount of network traffic features. Removing un...

Different Methods of Long-Term Electric Load Demand Forecasting a Comprehensive Review

Long-term demand forecasting presents the first step in planning and developing future generation, transmission and distribution facilities. One of the primary tasks of an electric utility accurately predicts load demand requirements at all times, especially for long-term. Based on the outcome of such forecasts, utilities coordinate their resources to meet the forecasted demand using a least-co...

ADAPTIVE ORDERED WEIGHTED AVERAGING FOR ANOMALY DETECTION IN CLUSTER-BASED MOBILE AD HOC NETWORKS

In this paper, an anomaly detection method in cluster-based mobile ad hoc networks with ad hoc on demand distance vector (AODV) routing protocol is proposed. In the method, the required features for describing the normal behavior of AODV are defined via step by step analysis of AODV and independent of any attack. In order to learn the normal behavior of AODV, a fuzzy averaging method is used fo...