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CANDECOMP/PARAFAC Decomposition (CPD) is one of the most popular tensor decomposition methods that has been extensively studied and widely applied. In recent years, sparse tensors that contain a huge portion of zeros but a limited number of non-zeros have attracted increasing interest. Existing techniques are not directly applicable to sparse tensors, since they mainly target dense ones and usually...
In competitive energy markets, the growing adoption of renewable energy sources such as wind energy and photovoltaics causes power grid fluctuations due to the intermittency and variability in their power output. To balance the demand and generation by renewable sources conventional thermal power plants must operate with greater flexibility in the way they increase or decrease output. Furthermore,...
Consider a microgrid with a hybrid collection of distributed energy resources (DERs) that include fossil, renewables and energy storage battery systems. Given the dynamic variability of the DERs in terms of power production, this paper presents an optimization approach for the optimal power dispatch in such a hybrid microgrid by taking into account amplitude and rate constraints on each DER. The constrained...
In robotics, non-linear least squares estimation is a common technique for simultaneous localization and mapping. One of the remaining challenges are measurement outliers leading to inconsistency or even divergence within the optimization process. Recently, several approaches for robust state estimation dealing with outliers inside the optimization back-end were presented, but all of them include...
In this paper, we first propose a Quality of Experience (QoE) evaluation model for dynamic adaptive streaming over HTTP (DASH) services. The proposed model predicts the perceived quality of user based on segment media quality, playback continuity and perceptual quality fluctuations caused by bitrate switching. Large quantities of subjective mean-opinion-score (MOS) tests demonstrate that our QoE evaluation...
We propose an action parsing algorithm to parse a video sequence containing an unknown number of actions into its action segments. We argue that context information, particularly the temporal information about other actions in the video sequence, is valuable for action segmentation. The proposed parsing algorithm temporally segments the video sequence into action segments. The optimal temporal segmentation...
This paper examines the tracking property of nonlinear delayed multi-agent systems with impulsive effects. The strengths and locations of the stabilizing impulses, as well as the number of the controlled nodes are all assumed to be time-varying. Some sufficient criteria are established such that the considered system can exponentially track the dynamical reference state based on the given impulsive...
Maximal Clique and Maximum Clique are two related and famous computational problems known to be intractable in the most general case. We propose a formulation of the Maximal Clique problem as a Boolean Satisfaction problem. The constraints are then mapped to a Constraint Logic Programming representation. The resulting representation can be input to a Constraint Logic Programming system that can be...
The solution of difficult problems can be realized in shorter time with heuristic algorithms. There are many heuristic algorithms. In this study, artificial bee colony (ABC), biogeography based optimization (BBO), cuckoo bird search algorithm (CSO), differential evolution (DE), imperialist competitive algorithm (ICA) and particle swarm algorithm (PSO) have been chosen due to reasons such as the widespread...
Restricted Boltzmann Machines (RBMs) have received special attention in the last decade due to their outstanding results in number of applications, such as face and human motion recognition, and collaborative filtering, among others. However, one of the main concerns about RBMs is related to the number of hidden units, which is application-dependent. Infinite RBM (iRBM) was proposed as an alternative...
In this study, crabs mating optimization (CRAB) algorithm that is one of the heuristic algorithms, has been developed and a monogamous crab mating optimization (MCO) algorithm has been proposed. In development, the main goal is to develop an algorithm that runs faster than the CRAB algorithm, to ensure obtaining good results like the CRAB algorithm. The developed MCO algorithm is compared with the...
In this study, the effect of distributions of solution candidates on the problem space in the meta-heuristic search process and the performance of algorithms has been investigated. For this purpose, solution candidates have been created with random and gauss (normal) distributions. Search performance is measured separately for both types of distribution of algorithms. The performances of the algorithms...
The increase in the size of the data used in natural language processing activities brings with it time and space constraints. Thus, it is important to both store and access data efficiently. This study includes experiments for storing the term-document index, which will be used in a natural language processing project, effectively in memory. For this purpose, the indexed data is compressed using...
Dynamic programming is an effective technique for the evaluation of the potential of optimal fuel consumption of drive trains, as it guarantees a globally optimal solution. This paper investigates two major problems associated with the application of dynamic programming. The first problem is the high computational complexity. Iterative dynamic programming is proposed as an alternative to dynamic programming...
The energy management is one of the most important issues for the efficiency and performance of the hybrid vehicular power system, including the Lithium-ion battery and Ultra-Capacitor. This paper deals with a dynamic programming based optimal control strategy proposed for the hybrid vehicular power system. The proposed method utilizes the capability of dynamic programming to treat the global optimization...
This paper gives a brief overview of the current state in the ant colony optimization (ACO) field of study. Furthermore, it introduces an alternative pheromone laying strategy for the ACO algorithm. In the paper, the newly introduced strategy is implemented, tested on a model problem and compared with the classical approach. A parameterized problem space generator has been introduced. The generator...
Mobile edge computing (MEC) has recently emerged as an important paradigm to bring computation and cache resources to the edge of core networks. However, the resources of edge network are relatively limited, so it is necessary to cooperate with data center (DC) which has sufficient computational resources. In this paper, we aim at designing a computation offloading and data caching model under the...
A lot of research has been proposed to improve network performance in the data center. However, with the development of distributed applications, these applications face a new performance bottleneck since existing solutions almost ignore the application level optimization. The concept of coflow has been proposed which provides a chance for us to optimize network in application level rather than individual...
In this paper, we investigate the quality of information (QoI) maximization problem by jointly optimizing the sampling rate, packet-dropped rate, and transmit power in wireless sensor networks (WSNs). We consider a complicated but practical scenario, where various tasks with heterogeneous traffic are supported by one WSN simultaneously. Accordingly, the QoI maximization problem is formulated as a...
How to reduce the energy consumption of urban rail transit system is always the focus of attention. The automatic train operation(ATO) system operates trains between successive stations by controlling the speed automatically, which is very important for the train energy saving operation. The traditional ATO recommended speed curve optimization research is based on line information, train information...
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