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...
Construction duration and schedule robustness are of great importance to ensure efficient construction. However, the current literature has neglected the importance of schedule robustness. Relatively little attention has been paid to schedule robustn...
Malicious attacks can cause significant damage to the structure and functionality of complex networks. Previous research has pointed out that the ability of networks to withstand malicious attacks becomes weaker when networks are coupled. However, tr...
Designing robust circuits that withstand environmental perturbation and device degradation is critical for many applications. Traditional robust circuit design is mainly done by tuning parameters to improve system robustness. However, the topological...
In this paper, an original modification of the generalised robust estimation of deformation from observation differences (GREDOD) method is presented with the application of two evolutionary optimisation algorithms, the genetic algorithm (GA) and gen...
Bluetooth Low Energy (BLE) is a popular wireless communication protocol heavily used in Internet of Things applications. Nowadays, robustness is considered a key requirement in wireless communication. However, radio interference from various sources...
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...
Regression models with change-points have been widely applied in various fields. Most methodologies for change-point regressions assume Gaussian errors. For many real data having longer-than-normal tails or atypical observations, the use of normal er...
In vehicle GNSS/INS integrated navigation, robust and adaptive algorithms have become one of the key technologies for achieving a comprehensive PNT due to their ability to control the gross errors of the observation model and dynamic model. The Sage&...
Based on a successive convex programming method, an alternating iteration algorithm is proposed for solving a parameter-dependent distributionally robust optimization. Under the Slater-type condition, the convergence analysis of the algorithm is obta...
The fraction of vegetation cover (FVC) is often estimated by unmixing a linear mixture model (LMM) to assess the horizontal spread of vegetation within a pixel based on a remotely sensed reflectance spectrum. The LMM-based algorithm produces results...
Due to the discreteness of integer data, there are a large number of gaps and continuous columns in the histogram based on integer data. Aiming at the characteristics, this paper presents a robust and reversible watermarking algorithm for a relationa...
Active headrest can reduce the low-frequency noise around ears based on the principle of active noise control. This paper presents a combination of robust algorithm and head-tracking for a feedforward active headrest to reduce the broadband noise for...
This study addresses the poor robustness of the current beamforming algorithm for covariance matrix reconstruction and the high computational complexity in the covariance matrix reconstruction process. A robust beamforming algorithm based on the Comp...
The paper deals with a robust sensor fault estimation by proposing a novel algorithm capable of reconstructing faults occurring in the system. The provided approach relies on calculating the fault estimation adaptively in every discrete time instance...
A robust multi-sensor recursive Expectation-Maximization (RMSREM) algorithm is proposed in this paper for autoregressive eXogenous (ARX) models, addressing the challenges of heavy-tailed noise, as well as the difficulty in simultaneously processing m...
The use of a cognitive radio power allocation algorithm is an effective method to improve spectral utilization. However, there are three problems with traditional cognitive radio power allocation algorithms: (1) based on the ideal channel model analy...
In recent years, Long-Term Evolution Vehicle-to-Everything (LTE-V2X) communication technology has received extensive attention. Timing synchronization is a crucial step in the receiving process, addressing Timing Offsets (TOs) resulting from random p...
A new approach to synthesize a robust controller for the angular motion of the Earth lander by decomposition method of output modal control is proposed. A universal analytical solution for the problem of stabilizing the angular position of the lander...
The recursive least-squares (RLS) algorithm stands out as an appealing choice in adaptive filtering applications related to system identification problems. This algorithm is able to provide a fast convergence rate for various types of input signals,...
At the time of writing, the COVID-19 infection is spreading rapidly. Currently, there is no vaccine or treatment, and researchers around the world are attempting to fight the infection. In this paper, we consider a diagnosis method for COVID-19, whic...
The assembly job shop scheduling problem (AJSSP) widely exists in the production process of many complex products. Robust scheduling methods aim to optimize the given criteria for improving the robustness of the schedule by organizing the assembly pr...
The design and optimization of the analog complementary metal-oxide-semiconductor (CMOS) integrated circuits (ICs) are intrinsically complicated and depend heavily on the designer’s experience, and are associated with very long design and optim...
In this paper, we propose a sparse distributionally robust optimization (DRO) model incorporating the Conditional Value-at-Risk (CVaR) measure to control tail risks in uncertain environments. The model utilizes sparsity to reduce transaction costs an...
The traditional consensus-based distributed economic dispatch strategy may lose system convergency and cause imbalanced power when facing an information attack on the individual power generation unit; thus, it is unable to achieve the dispatching goa...
Although light microscopy (LM) images are widely used to observe various bodily tissues, including salivary glands, reaching a satisfactory spatial resolution in the final images remains a major challenge. The objective of this study was to model a r...
Robust design problems in flow networks involve determining the optimal capacity assignments that enable the network to operate effectively even in the case of events’ occurrence such as arcs or nodes’ failures. Multi-source multi-sink fl...
Improving the stability of power systems using FACT devices is an important and effective method. This paper uses a static synchronous series compensator (SSSC) installed in a power system to smooth out inter-area oscillations. A meta-heuristic optim...
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...
Network robustness optimization is crucial for enhancing the resilience of industrial networks and social systems against malicious attacks. Existing studies typically evaluate the robustness by simulating the sequential removal of nodes or edges and...
In the field of energy networks, for their effective functioning, it is necessary to distribute the required load between all online generating units in a proper way to cover the demand. The load schedule is obtained by solving the so-called Economic...
Aiming at the problem of nonlinear observation model mismatch and insufficient anti-interference ability of SINS/GNSS integrated navigation system in complex dynamic environment, this paper proposes an adaptive robust filtering algorithm with improve...
In view of the complex and changeable operating environment of pumped storage power stations and the noise and outliers in the modeling data, this study proposes a sparse robust least squares support vector machine (LSSVM) model based on the hybrid b...
In the real world, forming a team of two or more people to solve a problem collaboratively is common to take advantage of the complementarity of the values and skills of team members. This idea can be used to develop more effective hybrid solution al...
Many transport systems in the real world can be modeled as networked systems. Due to limited resources, only a few nodes can be selected as seeds in the system, whose role is to spread required information or control signals as widely as possible. Th...
The highly efficient Interior Permanent Magnet Synchronous Motor (IPMSM) is ubiquitous choice in Electric Vehicles (EVs) for today’s automotive industry. IPMSM control requires accurate knowledge of an immeasurable critical Permanent Magnet (PM...
We propose a two-stage method to test the robustness of the generalized approximate message passing algorithm (GAMP). A pursuit process based on the marginal posterior probability is inserted in the standard GAMP algorithm to find the support of a sp...
Unmanned Aerial Vehicles (UAVs) are widely used in meteorology and logistics due to their unique advantages nowadays. During their lifecycle, uncertainties—such as flight condition variations—can significantly affect both design and perfo...
Traditional mean-variance (MV) models, considered effective in stable conditions, often prove inadequate in uncertain market scenarios. Therefore, there is a need for more robust and better portfolio optimization methods to handle the fluctuations an...
A sliding mode control (SMC) technique based on a state observer with a Kalman filter and feedforward controller was established for a variable-speed refrigeration system (VSRS) to ensure robust control against model uncertainties and disturbances, i...
China’s energy consumption issues are closely associated with global climate issues, and the scale of energy consumption, peak energy consumption, and consumption investment are all the focus of national attention. In order to forecast the amou...
This paper develops a two-stage robust optimization (TSRO) model for prosumers considering multiple uncertainties from the sustainable energy of wind power generation and load demand and extends the existing nested column-and-constraint generation (C...
Machine learning (ML) promises advances in automation and threat detection for the future generations of communication networks. However, new threats are introduced, as adversaries target ML systems with malicious data. Adversarial attacks on tree-ba...
Hybrid AC/DC microgrids (HADCMGs), which integrate renewable energy sources and battery storage systems, often face significant stability challenges due to their inherently low inertia and highly variable power inputs. To address these issues, this p...
In this work, the quantum random walk search algorithm with a walk coin constructed by generalized Householder reflection and phase multiplier has been studied. The coin register is one qudit with an arbitrary dimension. Monte Carlo simulations, in c...
In this study, we introduce a novel collaborative federated learning (FL) framework, aiming at enhancing robustness in distributed learning environments, particularly pertinent to IoT and industrial automation scenarios. At the core of our contributi...
The proportional integral derivative (PID) controller is one of the most robust and simplest configuration controllers used for industrial applications. However, its performance purely depends on the tuning of its proportional (KP), integral (KI) and...
An improved affine projection sign algorithm (APSA) was developed herein using a
In order to address the issues of system fluctuation and low efficiency brought on by various disturbance factors in wastewater treatment plants (WWTPs), this study builds a robust multi-objective optimization model and determines the ideal parameter...
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...
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