Multi-source autonomous navigation-dependable decision making has a crucial impact on the overall performance of navigation systems. To solve the problem of overall system robustness caused by the intelligent-dependable decision making difficulties o...
Automatic age estimation from unconstrained facial images is a challenging task and it recently has gained much attention due to its wide range of applications. In this paper, we propose a new model based on convolutional neural networks (CNNs) and l...
In this paper, we propose informed weighted non-negative matrix factorization (NMF) methods using an
The non-redescending convex functions degrade the filtering robustness, whereas the redescending non-convex functions improve filtering robustness, but they tend to converge towards local minima. This work investigates the properties of convex and no...
This paper proposes a robust optimization algorithm customized for the optimal design of electric machines. The proposed algorithm, termed “robust explorative particle swarm optimization” (RePSO), is a hybrid algorithm that affords high accuracy and...
The design of a structure is generally carried out according to a deterministic approach. However, all structural problems have associated initial uncertain parameters that can differ from the design value. This becomes important when the goal is to...
For microgrids with uncertainties in renewable energy generation and normal load demand, a robust multi-objective and multi-scenario performance optimization algorithm based on lexicographic order is proposed, which considers system economic cost, en...
For active control of impulsive noise, the conventional filtered-x least mean square (FxLMS) algorithm has poor noise reduction performance. To address this issue, this paper designs a robust cost function by embedding the cost function of the FxLMS...
This paper investigates various supply chain disruptions in terms of scenario planning, including node disruption and chain disruption; namely, disruptions in distribution centers and disruptions between manufacturing centers and distribution centers...
In active noise control (ANC) systems, the traditional filtered-x least mean square (FxLMS) algorithm has poor control effect on impulsive noise. To overcome this drawback, a robust cost function was designed in this paper by embedding the cost funct...
The uncertainty of post-earthquake disaster situations can affect the efficiency of rescue site selection, material, and personnel dispatching, as well as the sustainability of related resources. It is crucial for decision-makers to make decisions to...
21 October 2022
This paper proposes an operating room (OR) scheduling model to assign a group of next-day patients to ORs while adhering to OR availability, priorities, and OR overtime constraints. Existing studies usually consider OR scheduling problems by ignoring...
In most practical applications, the tracking process needs to update the data constantly. However, outliers may occur frequently in the process of sensors’ data collection and sending, which affects the performance of the system state estimate....
Scaling of the cost-functional and its violations are discussed with regard to their application to the summation of asymptotic truncated expansions. A new family of cost-functionals dependent only on amplitudes is considered, allowing for a continuo...
This research focuses on designing a min–max robust control based on a neural dynamic programming approach using a class of continuous differential neural networks (DNNs). The proposed controller solves the robust optimization of a proposed cos...
Three-dimensional (3D) reconstruction using RGB-D camera with simultaneous color image and depth information is attractive as it can significantly reduce the cost of equipment and time for data collection. Point feature is commonly used for aligning...
Following various natural and man-made disasters, a critical challenge in emergency response is establishing an emergency living supplies distribution center that minimizes service costs while ensuring rapid and efficient delivery of essential goods...
In this paper, a robust differential game guidance law is proposed for the nonlinear zero-sum system with unknown dynamics and external disturbances. First, the continuous-time nonlinear zero-sum differential game problem is transformed into solving...
A novel multi-objective robust optimization model of an integrated energy system with hydrogen storage (HIES) considering source–load uncertainty is proposed to promote the low-carbon economy operation of the integrated energy system of a park....
In this paper, we introduce a new class of multi-dimensional robust optimization problems (named
In this paper, a multiobjective approach to carry out the planning of medium-voltage (MV) and low-voltage (LV) distribution systems, considering renewable energy sources (RES) and robustness, is proposed. Due to the uncertainties associated with RES...
The performance of low-cost smart terminals is limited by the performance of their low-cost Global Navigation Satellite System (GNSS) hardware and chips, as well as by the impact of complex urban environments, which affect the positioning accuracy an...
A novel robust particle filtering algorithm is proposed for updating both the waveform and noise parameter for tracking accuracy simultaneously and adaptively. The approach is a significant step for cognitive radar towards more robust tracking in ran...
Extrapolation of the asymptotic series with a cost functional imposed on iterated Borel summation is considered. The cost functionals are designed to determine the optimal control parameter, the role of which is performed by the number of iterations,...
Robustness and evolvability are essential properties to the evolution of biological networks. To determine if a biological network is robust and/or evolvable, it is required to compare its functions before and after mutations. However, this sometimes...
In the field of image steganography research, more and more attention is paid to the importance of stego image robustness. In order to make steganography accessible from laboratory to practical applications, it becomes critical that the stego images...
As an emerging energy allocation method, shared energy storage devices play an important role in modern power systems. At the same time, with the continuous improvement in renewable energy penetration, modern power systems are facing more uncertainti...
Convolutional neural networks (CNNs) can efficiently extract image features and perform corresponding classification. Typically, the CNN architecture uses the softmax layer to map the extracted features to classification probabilities, and the cost f...
This paper presents a segmentation-based stereo matching algorithm using an adaptive multi-cost approach, which is exploited for obtaining accuracy disparity maps. The main contribution is to integrate the appealing properties of multi-cost approach...
Achieving consensus in group decision-making is both essential and challenging, especially in which non-cooperative behaviors can significantly hinder the process under uncertainty. These behaviors may distort consensus outcomes, leading to increased...
This paper presents a novel framework for economic cooling load dispatch in conventional water-cooled chillers. Moreover, information gap decision theory (IGDT) is applied to the optimal chiller loading (OCL) problem to find the optimum operating poi...
We study the sufficient optimality conditions for a class of fractional variational control problems involving data uncertainty in the cost functional. Concretely, by using the parametric technique, we prove the sufficiency of the robust necessary op...
We present an efficient and accurate computational algorithm for reconstructing a local volatility surface from given market option prices. The local volatility surface is dependent on the values of both the time and underlying asset. We use the gene...
We propose a framework using contrastive learning as a pre-training task to perform image classification in the presence of noisy labels. Recent strategies, such as pseudo-labeling, sample selection with Gaussian Mixture models, and weighted supervis...
This paper introduces a novel framework for Distributionally Robust Bayesian Optimization (DRBO) with continuous context that integrates optimal transport theory and entropic regularization. We propose the sampling from the Wasserstein Barycenter Bay...
This paper addresses the feasibility of implementing spatial diversity techniques to mitigate interference signals using low-cost GNSS receivers. Global Navigation Satellite Systems (GNSSs) remain at the core of navigation technologies and obtaining...
Designing the future energy supply in accordance with ambitious climate change mitigation goals is a challenging issue. Common tools for planning and calculating future investments in renewable and sustainable technologies are often linear energy sys...
This paper describes the basic ideas behind a novel prediction error parameter identification algorithm exhibiting high robustness with respect to outlying data. Given the low sensitivity to outliers, these can be more easily identified by analysing...
Time difference of arrival (TDOA) based indoor ultrasound localization systems are prone to multiple disruptions and demand reliable, and resilient position accuracy during operation. In this challenging context, a missing link to evaluate the perfor...
Variable-speed pumped storage has the advantages of flexible adjustment and low economic cost, which can reduce the adverse effects caused by a high proportion of new energy access. In order to reduce the system operation risk caused by the randomnes...
The development of multimodal transport has had a significant impact on China’s transportation industry. Due to the variability of the market environment, in this study, based on the context of the official launch of the national carbon emissio...
The structural design of civil works is closely tied to empirical knowledge and the design professional’s experience. Based on this, adequate designs are generated in terms of strength, operability, and durability. However, such designs can be...
Reliable and affordable data acquisition is crucial in industrial applications and critical infrastructure monitoring. However, common low-cost sensors with an I2C interface have limited range and low resistance to interference, which limits their de...
Independent component analysis (ICA), as a statistical and computational approach, has been successfully applied to digital signal processing. Performance analysis for the ICA approach is perceived as a challenging task to work on. This contribution...
The authors of this paper propose a robust star identification algorithm for a ‘Lost-In-Space’-mode star tracker for lost-cost CubeSat missions. A two-step identification framework and an embedded validation mechanism were designed to acc...
In this study, based on the policy iteration (PI) in reinforcement learning (RL), an optimal adaptive control approach is established to solve robust control problems of nonlinear systems with internal and input uncertainties. First, the robust contr...
The effective design of nearly zero-energy buildings depends on a large set of interdependent variables, which affect both energy demand and supply. Considering them simultaneously is fundamental when searching for optimal design of nearly zero-energ...
Image interleaving has proven to be an effective solution to provide the robustness of image communication systems when resource limitations make reliable protocols unsuitable (e.g., in wireless camera sensor networks); however, the search for optima...
In this paper, a robust trajectory tracking control method with state constraints and uncertain disturbances on the ground of adaptive dynamic programming (ADP) is proposed for nonlinear systems. Firstly, the augmented system consists of the tracking...
In this work, we studied the area coverage control problem (ACCP) based on the time cost metric of a robot network with an input disturbance in a dynamic environment, which was modeled by a time-varying risk density function. A coverage control metho...
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