Electrical plug loads comprise an increasingly larger share of building energy consumption as improvements have been made to Heating, Ventilation, and Air Conditioning (HVAC) and lighting systems. It is anticipated that plug loads will account for a significant portion of the energy consumption of Sustainability Base, a recently constructed high-performance office building at NASA Ames Research...

Short-term load forecasting (STLF) is an essential procedure for effective and efficient realtime operations planning and control of generation within a power system. It provides the basis for unit-commitment and power system planning procedures, maintenance schedul‐ ing, system security assessment, and trading schedules. It establishes the generation, capaci‐ ty, and spinning reserve schedules...

Prediction techniques are an interesting challenge in many areas like weather, banking, and finance, healthcare and so on. They are also becoming a popular subject in networking domain. This topic explores link load prediction of a network using Support Vector Regression and Optimization techniques. Support Vector Regression(SVR) is robust to outliers and can be used to online and adaptive lear...

With the increasing interest in deploying 4G/LTE network, IMS has a potential to be deployed in wide scale in order to support mobile Internet and value-added services over next-generation networks. Moreover, the effort to create an operator-controlled signaling infrastructure using IP-based protocols has resulted in a large number of functional components and interactions between core networks...

Parallel scienti c computing in a distributed computing environment based on CORBA requires additional services not (yet) included in the CORBA speci cation: load distribution and fault tolerance. Both of them are essential for long running applications with high computational demands as in the case of computational engineering applications. The proposed approach for providing these services is...

Electricity load forecasting is an important issue that is widely explored and examined in power systems operation literature and commercial transactions in electricity markets literature as well. Among the existing forecasting models, support vector regression (SVR) has gained much attention. Considering the performance of SVR highly depends on its parameters; this study proposed a firefly alg...

Based on the Nyström approximation and the primal-dual formulation of Least Squares Support Vector Machines (LS-SVM), it becomes possible to apply a nonlinear model to a large scale regression problem. This is done by using a sparse approximation of the nonlinear mapping induced by the kernel matrix, with an active selection of support vectors based on quadratic Renyi entropy criteria. The meth...

Non-intrusive load monitoring (NILM) is a promising approach to provide energy consumption of electrical appliances and analysis current voltage data with less instrumentation. This paper proposes an classification model using support vector machine (SVM). SVM was chosen keep the computational cost low be able implement embedded system. The utilized classify on/off state air conditioners, light...

based on the problems caused by today conventional vehicles, much attention has been put on the fuel cell vehicles researches. however, using a fuel cell system is not adequate alone in transportation applications, because the load power profile includes transient that is not compatible with the fuel cell dynamic. to resolve this problem, hybridization of the fuel cell and energy storage device...