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The ever-increasing complexity in power systems requires novel optimization and control tools. These tools must be validated prior to application to real power systems. Such validation requires access to a realistic, high fidelity power system network model. Fuel cost is an important element for such a model, but is often difficult to obtain due to confidentiality constraints. This paper advances...
Modern chemical processes are usually characterized by large-scale, complex correlation, and strong dynamics, and monitoring of such processes is imperative. This paper proposes a performance-driven fault-relevant dynamic principal component (FRDPC) subspace construction integrated with Bayesian inference method to achieve efficient monitoring for dynamic chemical processes. First, dynamic principal...
Cluster analysis is important in scientific and industrial fields. In this study, we proposed a novel chaotic biogeography-based optimization (CBBO) method, and applied it in centroid-based clustering methods. The results over three types of simulation data showed that this proposed CBBO method gave better performance than chaotic particle swarm optimization, genetic algorithm, firefly algorithm,...
Many recent scientific efforts have been devoted to constructing the human connectome using Diffusion Tensor Imaging (DTI) data for understanding large-scale brain networks that underlie higher-level cognition in human. However, suitable network analysis computational tools are still lacking in human brain connectivity research. To address this problem, we propose a novel probabilistic multi-graph...
Any evolutionary algorithms should conduct biased search in the search space. Most popular strategies for doing so focus on how to select and generate solutions. In this paper, a new strategy is proposed. It completes the task through the transformation of the given problem. A population of converted problem responding various search weights is used, which may be more suitable for evolutionary algorithm...
The latest high efficiency video coding (HEVC) standard achieves about 50% bit-rate reduction at equivalent visual quality compared to H.264/AVC. Sample adaptive offset (SAO) is one of the newly adopted tools right after deblocking filter, which can improve both coding efficiency and visual quality. However, for real-time encoding scenarios, the complexity of SAO is usually too high to be enabled...
The problem of linear guideway cutting is an one-dimensional cutting stock problem in making a production plan, which significantly affects enterprises performance on material usage and production costs. In this paper, the practical features in an actual production environment are analyzed with regard to stock length, holes distance, edges distance, cutting scrap, cutting direction, scrap usage, etc...
Channel-width adaptation can significantly improve the connectivity, capacity and reduce the power consumption in wireless networks. The OFDMA-based channel-width adaptation based on traffic demand has been studied in wireless networks with sufficient spectral resources. However, the traffic demand may not be fully satisfied in resource-limited scenarios. In this paper, we study the channel-width...
Although 2.5D IC, in which chips are connected via the interposer, can increase circuit density and performance, power dissipation and thermal effect become serious concerns for 2.5D IC design. Previous researches only focus on the power and thermal management of a single chip. Therefore, in the existing 2.5D IC design flow, the designer has no idea on the power budget of each chip. Based on this...
This paper describes a Discrete Event Simulation (DES) model for a hypothetical inpatient flow process of a large acute-care hospital. The implementation of the Multi-Objectives Convergent Optimization via Most-Promising-Area Stochastic Search (MO-COMPASS) approach in this DES model for the identification of promising Pareto optimal solutions is also discussed. The MO-COMPASS algorithm implemented...
We propose a community detection method based on K-shell. Our method determines some core nodes of the graph according to the K-shell value of these nodes. These core nodes constitute a subgraph on which we use the community detection algorithm to divide the core nodes into communities. Compared to classical methods, by this way, our proposed method removes the non-core nodes which may impact the...
Emulsion polymerization is an economically important method of producing a number of polymer products, where particle size distribution (PSD) is an essential property of the latex produced. A programming-based approach has been proposed for reachability analysis of PSD for a general particulate system described by population balance models, along with application to a semibatch styrene homopolymerization...
A perpendicular multi-layer (PML) architecture with multiple controllers and a dynamic orchestra plane (DOP) for multi-domain software defined optical networks is proposed in this paper. Cross-domain services with on-demand bandwidth can be deployed via unified interfaces provided by DOP. Practical capture of signal processing and emulation results are presented.
The increasing number of plug-in electric vehicles (PEVs) will post new challenges to the existing power grid, as they as a whole will become a substantially large load to the power grid when they are being charged. In this paper, an algorithm is proposed to maximize the injection of PEVs in distribution networks (DNs) without violating power limitations and causing voltage problems. This method is...
We present a hierarchical computation approach for solving finite-time optimal control problems using operator splitting methods. The first split is performed over the time index and leads to as many subproblems as the length of the prediction horizon. Each subproblem is solved in parallel and further split into three by separating the objective from the equality and inequality constraints respectively,...
In this paper we introduce a control policy which we refer to as the iterated approximate value function policy. The generation of this policy requires two stages, the first one carried out off-line, and the second stage carried out on-line. In the first stage we simultaneously compute a trajectory of moments of the state and action and a sequence of approximate value functions optimized to that trajectory...
Artificial bee colony (ABC) algorithm invented recently by Karaboga is a competitive stochastic population-based optimization algorithm. However, solution search equation used in the original ABC algorithm is good at exploration but poor at exploitation. an improved ABC algorithm called Gbest-guided ABC (GABC) was introduced by researchers to improve the exploitation of ABC algorithm. in order to...
Particle swarm optimization (PSO) has been proposed as an alternative to traditional evolutionary algorithms. In this work, we present a new PSO approach to control the trade-off between exploitation and exploration in the search process for solving multimodal functions. Our approach focuses on two search strategies for multimodal functions. One is a two-swarm cooperative strategy that controls search...
Multiple-Instance learning (MIL), which relaxes training annotation granularity from instance level to instance collection (bag) level by applying bag concept, obtains increasing attentions from computer vision community. Due to its flexible annotation mechanism, MIL has been naturally utilized on a variety of computer vision problems. And numerous models have been proposed, each of which is ingeniously...
The performances of supervised learning techniques on image classification problems heavily rely on the quality of their training images. But the acquisition of high quality training images requires significant efforts from human annotators. In this paper, we propose a novel multi-label batch model active learning (MLBAL) approach that allows the learning algorithm to actively select a batch of informative...
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