Search Results (251)

This paper proposes a novel mixed game-based day-ahead operation strategy for multi-building integrated energy systems, which innovatively addresses both inter-building cooperation and non-cooperative energy transactions with system operators under uncertainties. Specifically, a bi-level operation model is established in which the upper level maximizes the benefits of the energy system operator, and the lower level minimizes the costs of multiple buildings. Then, in consideration of source-load uncertainties in multiple building energy systems, the fuzzy chance-constrained programming method is introduced, and the clear equivalent class method is used to reformulate the fuzzy chance constrained model into a tractable deterministic type. Further, a privacy-preserving hierarchical solution approach is presented to solve the bi-level optimization model, and the Shapley value method is adopted for benefits redistribution. Case studies on a multi-building system in East China showcase the effectiveness of the proposed work and demonstrate that the proposed strategy contributes to reducing the operation costs of the multi-building system by approximately 3.98% and increasing the revenue of the energy system operators by 10.31%. Full article

Firmware vulnerabilities in embedded devices have caused serious security incidents, necessitating similarity analysis of binary program instruction embeddings to identify vulnerabilities. However, existing instruction embedding methods neglect program execution semantics, resulting in accuracy limitations. Furthermore, current embedding approaches utilize independent computation across models, where the lack of standardized interaction information between models makes it difficult for embedding models to efficiently detect firmware vulnerabilities. To address these challenges, this paper proposes a firmware vulnerability detection scheme based on statistical inference and code similarity fuzzy matching analysis for resource-constrained vehicular network environments, helping to balance both accuracy and efficiency. First, through dynamic programming and neighborhood search techniques, binary code is systematically partitioned into normalized segment collections according to specific rules. The binary code is then analyzed in segments to construct semantic equivalence mappings, thereby extracting similarity metrics for function execution semantics. Subsequently, Google Protocol Buffers (ProtoBuf) is introduced as a serialization format for inter-model data transmission, serving as a “translation layer” and “bridging technology” within the firmware vulnerability detection framework. Additionally, a ProtoBuf-based certificate authentication scheme is proposed to enhance vehicular network communication reliability, improve data serialization efficiency, and increase the efficiency and accuracy of the detection model. Finally, a vehicular network simulation environment is established through secondary development on the NS-3 network simulator, and the functionality and performance of this architecture were thoroughly tested. Results demonstrate that the algorithm possesses resistance capabilities against common security threats while minimizing performance impact. Experimental results show that FirmPB delivers superior accuracy with 0.044 s inference time and 0.932 AUC, outperforming current SOTA in detection performance. Full article

This paper introduces a framework of hypercompositional algebra on fuzzy graphs by defining and analyzing fuzzy path-based hyperoperations. Building on the notion of strongest strong paths (paths that are both strength-optimal and composed exclusively of strong edges, where each edge achieves maximum connection strength between its endpoints), we define two operations: a vertex-based fuzzy path hyperoperation and an edge-based variant. These operations generalize classical graph hyperoperations to the fuzzy setting while maintaining compatibility with the underlying topology. We prove that the vertex fuzzy path hyperoperation is associative, forming a fuzzy hypersemigroup, and establish additional properties such as reflexivity and monotonicity with respect to $\alpha$-cuts. Structural features such as fuzzy strong cut vertices and edges are examined, and a fuzzy distance function is introduced to quantify directional connectivity strength. We define an equivalence relation based on mutual full-strength reachability and construct a quotient fuzzy graph that reflects maximal closed substructures under the vertex fuzzy path hyperoperation. Applications are discussed in domains such as trust networks, biological systems, and uncertainty-aware communications. This work aims to lay the algebraic foundations for further exploration of fuzzy hyperstructures that support modeling, analysis, and decision-making in systems governed by partial and asymmetric relationships. Full article

In this paper, we investigate a class of fuzzy partially differentiable models for Caputo–Hadamard-type Goursat problems with generalized Hukuhara difference, which have been widely recognized as having a significant role in simulating and analyzing various kinds of processes in engineering and physical sciences. By transforming the fuzzy partially differentiable models into equivalent integral equations and employing classical Banach and Schauder fixed-point theorems, we establish the existence and uniqueness of solutions for the fuzzy partially differentiable models. Furthermore, in order to overcome the complexity of obtaining exact solutions of systems involving Caputo–Hadamard fractional derivatives, we explore numerical approximations based on trapezoidal and Simpson’s rules and propose three numerical examples to visually illustrate the main results presented in this paper. Full article

To address the challenges in predicting roof water hazards in weakly cemented strata of Northwest China, this study pioneers an integrated CNN-BiLSTM model for aquifer water abundance prediction. Focusing on the 1301E working face in the Yili No. 1 Coal Mine, we employed kriging interpolation to process sparse hydrological datasets (mean relative error: 8.7%), identifying five dominant controlling factors—aquifer burial depth, hydraulic conductivity, core recovery rate, sandstone–mudstone interbedded layer count, and sandstone equivalent thickness. The proposed bidirectional architecture synergizes CNN-based spatial feature extraction with BiLSTM-driven nonlinear temporal modeling, optimized via Bayesian algorithms to determine hyperparameters (32-channel convolutional kernels and 64-unit BiLSTM hidden layers). This framework achieves the comprehensive characterization of multifactorial synergistic effects. The experimental results demonstrate: (1) that the test set root mean square error (1.57 × 10⁻³) shows 65.3% and 85.9% reductions compared to the GA-BP and standalone CNN models, respectively; (2) that the coefficient of determination (R² = 0.9966) significantly outperforms the conventional fuzzy analytic hierarchy process (FAHP, error: 0.071 L/(s·m)) and BP-based neural networks; (3) that water abundance zoning reveals predominantly weak water-rich zones (q = 0.05–0.1 L/(s·m)), with 93.3% spatial consistency between predictions and pumping test data. Full article

As an emerging marketing tool, virtual influencers (VIs) have attracted increasing scholarly attention. However, existing research predominantly adopts linear causal analysis models, which fail to capture the complex, nonlinear interaction between consumers and VIs. Grounded in the 5W communication model and utilizing a fuzzy-set qualitative comparative analysis (fsQCA), this study systematically explores how different configurational paths influence consumer engagement, drawing on empirical data from 205 participants. The findings reveal that (1) the synergy of entertainment, information, and credibility is a core prerequisite for achieving high engagement; (2) two equivalent paths—namely, the technology-driven path (media richness + content synergy) and the cognition-driven path (technology acceptance + content synergy)—lead to high engagement, both with a solution consistency of 0.98; and (3) the joint absence of content, media richness, and audience cognition results in low engagement. Theoretically, this study challenges traditional linear approaches by validating causal asymmetry and revealing configurational interdependencies among communication elements. It also extends the Media Richness Theory (MRT) and the Technology Acceptance Model (TAM) into the context of virtual influencer (VI) marketing. Practically, the proposed dynamic configuration model offers marketers a novel framework for optimizing VI campaigns through resource-adaptive strategies. Full article

The rapid development of the new energy vehicle industry has resulted in a significant number of waste electric vehicle batteries (WEVBs) reaching the end of their useful life. The recycling of these batteries holds both economic and environmental value. As policy is a critical factor influencing the recycling of waste electric vehicle batteries, its role in the network warrants deeper investigation. Based on this, this study integrates both subsidy and penalty policy into the design of the waste electric vehicle battery reverse logistics network (RLN), aiming to examine the effects of single policy and policy combinations, thereby filling the research gap in the existing literature that predominantly focuses on single-policy perspectives. Considering multiple battery types, different recycling technologies, and uncertain recycling quantities and qualities, this study develops a fuzzy mixed-integer programming model to optimize cost and carbon emission. The fuzzy model is transformed into a deterministic equivalent form using expected intervals, expected values, and fuzzy chance-constrained programming. By normalizing and weighting the upper and lower bounds of the multi-objective functions, the model is transformed into a single-objective optimization problem. The effectiveness of the proposed model and solution method was validated through an empirical study on the construction of a waste electric vehicle battery reverse logistics network in Zhengzhou City. The experimental results demonstrate that combined policy outperforms single policy in balancing economic benefits and environmental protection. The results provide decision-making support for policymakers and industry stakeholders in optimizing reverse logistics networks for waste electric vehicle batteries. Full article

Against the intensifying mismatch between urban and rural land resources, activating farmers’ intentions to revitalize their idle homesteads is a key issue in optimizing land resource allocation and promoting urban–rural integrated development. However, existing studies mostly focus on the marginal effect of a single factor and ignore the synergistic effect of multiple factors, making it difficult to reveal the complex causal logic of farmers’ decision-making. This study aims to explain the causal asymmetry and equivalent path problem in farmers’ revitalized decision-making by capturing the multidimensional interaction mechanism of “external stimulus–mental cognition”. This study integrates the social stratification theory, the theory of planned behavior, and the Stimulus–Organism–Response framework to systematically explore how the interactive configuration of farmer differentiation and cognition from a multidimensional perspective drives the formation of farmers’ willingness to engage in high inventory activities, based on the 881 farmer research data in Shaanxi Province, using fuzzy-set qualitative comparative analysis (fsQCA) methodology. This study found that (1) a single condition cannot independently explain the intentions of farmers to revitalize, and its formation needs to rely on the synergistic linkage of multiple conditions; (2) the configuration of farmers’ high intentions to revitalize includes “wealth capital differentiation–dual cognitive-driven type”, “single cognitive-driven type”, “reputation capital differentiation–single cognitive-driven type”, “wealth capital differentiation–single cognitive-driven type”, which wealth capital differentiation is the common core condition triggering high intention; and (3) the formation of farmers’ low revitalization intentions stems from the insufficient differentiation of farmers and the lack of cognitive elements. Therefore, policymakers should take a holistic perspective in enhancing farmers’ revitalization intentions, focusing on the rational allocation between farmer differentiation and farmers’ cognition. Full article

We reformulate holographic space–time models in terms of Hilbert bundles over the space of the time-like geodesics in a Lorentzian manifold. This reformulation resolves the issue of the action of non-compact isometry groups on finite-dimensional Hilbert spaces. Following Jacobson, I view the background geometry as a hydrodynamic flow, whose connection to an underlying quantum system follows from the Bekenstein–Hawking relation between area and entropy, generalized to arbitrary causal diamonds. The time-like geodesics are equivalent to the nested sequences of causal diamonds, and the area of the holoscreen (The holoscreen is the maximal $d-2$ volume (“area”) leaf of a null foliation of the diamond boundary. I use the term area to refer to its volume.) encodes the entropy of a certain density matrix on a finite-dimensional Hilbert space. I review arguments that the modular Hamiltonian of a diamond is a cutoff version of the Virasoro generator $L_0$ of a $1+1$-dimensional CFT of a large central charge, living on an interval in the longitudinal coordinate on the diamond boundary. The cutoff is chosen so that the von Neumann entropy is $\ln {\mathrm{D}}_{\diamond },$ up to subleading corrections, in the limit of a large-dimension diamond Hilbert space. I also connect those arguments to the derivation of the ’t Hooft commutation relations for horizon fluctuations. I present a tentative connection between the ’t Hooft relations and $U\left(1\right)$ currents in the CFTs on the past and future diamond boundaries. The ’t Hooft relations are related to the Schwinger term in the commutator of the vector and axial currents. The paper in can be read as evidence that the near-horizon dynamics for causal diamonds much larger than the Planck scale is equivalent to a topological field theory of the ’t Hooft CR plus small fluctuations in the transverse geometry. Connes’ demonstration that the Riemannian geometry is encoded in the Dirac operator leads one to a completely finite theory of transverse geometry fluctuations, in which the variables are fermionic generators of a superalgebra, which are the expansion coefficients of the sections of the spinor bundle in Dirac eigenfunctions. A finite cutoff on the Dirac spectrum gives rise to the area law for entropy and makes the geometry both “fuzzy” and quantum. Following the analysis of Carlip and Solodukhin, I model the expansion coefficients as two-dimensional fermionic fields. I argue that the local excitations in the interior of a diamond are constrained states where the spinor variables vanish in the regions of small area on the holoscreen. This leads to an argument that the quantum gravity in asymptotically flat space must be exactly supersymmetric. Full article

This study was conducted to achieve simple and feasible secondary-side independent power control for wireless power transfer (WPT) systems with a hybrid energy storage system (HESS) and to minimize the power loss introduced by the added converter. We propose a novel operation mode tailored to a WPT system with a HESS load composed of an LCC-compensated WPT system and a Buck/Boost bidirectional converter. Its power control is based on insights into the characteristics of LCC–LCC compensation. Since this control method requires the cooperation of a DC converter, control of the converter’s efficiency is the focus of this paper. Building on this framework, several parasitic parameters such as the equivalent series resistance (ESR) of inductors and switches are taken into account. An improved operation mode is proposed to address the efficiency degradation and control imbalance caused by ESR. By meticulously controlling the behavior of the components of the converter, the devices operate in zero-voltage switching (ZVS) mode, thereby reducing switching losses. Additionally, fuzzy control is utilized in this study to enhance robustness. The analyses are verified through a prototype system. The results of the experiments illustrate that the analytical approach proposed in this study achieves reliable power control and efficient converter operation. The results of this study show that the efficiency of the devices is improved and reached up to 99% with the converter. This study explores the efficiency optimization of the WPT system, which directly supports sustainable practices by reducing resource consumption and minimizing environmental impact. The findings offer valuable insights into sustainable applications and policy implications, aligning with the goals of socio-economic and environmental sustainability. Full article

In this paper, we investigate the evolution characteristics of floor failure during pressured mining in extra-thick coal seams. A mechanical expression relating floor failure depth to seam thickness is established based on soil mechanics and mine pressure theory. The findings reveal a linear relationship between seam thickness and floor failure depth; specifically, as the coal seam thickens, the depth of floor failure increases. To simulate the mining process of extra-thick coal seams, FLAC3D numerical simulation software is utilized. We analyze the failure process, failure depth, and the behavior of water barriers at the coal seam floor under the influence of extra-thick coal seam mining from three perspectives: rock displacement evolution in the floor, stress evolution in the floor, and plastic deformation. Based on geological characteristics observed in the Longwanggou mine field, we establish a main control index system for assessing floor water-inrush risk. This system comprises 11 primary control factors: water abundance, permeability, water pressure, complexity of geological structure, structural intersection points, thickness of both actual and equivalent water barriers, thickness ratio of brittle–plastic rocks to coal seams, as well as depths related to both coal seams and instances of floor failure. Furthermore, drawing upon grey system theory and fuzzy mathematics within uncertainty mathematics frameworks leads us to propose an innovative approach—the interval grey optimal clustering model—designed specifically for risk assessment concerning potential floor water inrush during pressured mining operations involving extra-thick coal seams. This method of mine water inrush risk assessment is applicable for popularization and implementation in mines with analogous conditions, and it holds practical significance for the prevention of mine water damage. Full article

The flexible job shop scheduling problem is relevant in many different areas. However, the usual deterministic approach sees its usefulness limited, as uncertainty plays a paramount role in real-world processes. Considering processing times in the form of fuzzy numbers is a computationally affordable way to model uncertainty that enhances the applicability of obtained solutions. Unfortunately, fuzzy processing times add an extra layer of complexity to otherwise straightforward operations. For example, in energy-aware environments, measuring the idle times of resources is of the utmost importance, but it goes from a trivial calculation in the deterministic setting to a critical modelling decision in fuzzy scenarios, where different approaches are possible. In this paper, we analyse the drawbacks of the existing translation of the deterministic approach to a fuzzy context and propose two alternative ways of computing the idle times in a schedule. We show that, unlike in the deterministic setting, the different definitions are not equivalent when fuzzy processing times are considered, and results are directly affected, depending on which one is used. We conclude that the new ways of computing idle times under uncertainty provide more reliable values and, hence, better schedules. Full article

Carrier-based aircraft (CBA) landing involves complex system engineering characterized by strong non-linearity, significant coupling and susceptibility to environmental disturbances. To address uncertainties in parameters, carrier air-wake disturbances and other challenges inherent to CBA landing, this paper presents a longitudinal automatic landing system based on adaptive fuzzy sliding-mode control. This system was developed to improve control accuracy and stability during the critical landing phase. Furthermore, this paper analyzes components of carrier air-wake and motion conditions for ideal landing points on the carrier deck, and designs a sliding-mode surface with the integral term. An adaptive fuzzy sliding-mode controller based on equivalent and switching controls is constructed, which exhibits stability under the Lyapunov stability condition. Moreover, a Monte Carlo simulation method is employed to verify the simulation of the automatic landing control system. Owing to its impressive dynamic performance and robustness, the proposed control method can track expected values with high accuracy in a complex environment, thereby satisfying the CBA landing requirements. Full article

Continuous and accurate state-of-charge estimation is essential for optimal reliability and performance in electric vehicle battery management systems. This work reviews state-of-charge estimation strategies, from straightforward methods like lookup tables and ampere-hour counting to advanced mathematical models, such as electrochemical, observer-assisted equivalent circuit, and impedance-based models that capture cell dynamics. Additionally, data-driven models including fuzzy logic, neural networks, and support vector machines are explored for their ability to leverage large datasets. This review highlights the strengths and limitations of each method, emphasizing the specific contexts in which these strategies can be applied to achieve optimal effectiveness. Full article

To address the challenges faced by fuel cell hybrid electric tractors (FCHETs) equipped with a battery and supercapacitor, including the complex coordination of multiple energy sources, low power allocation efficiency, and unclear optimal energy consumption, this paper proposes two energy management strategies (EMSs): one based on hierarchical instantaneous optimization (HIO) and the other based on multi-dimensional dynamic programming with final state constraints (MDDP-FSC). The proposed HIO-based EMS utilizes a low-pass filter and fuzzy logic correction in its upper-level strategy to manage high-frequency dynamic power using the supercapacitor. The lower-level strategy optimizes fuel cell efficiency by allocating low-frequency stable power based on the principle of minimizing equivalent consumption. Validation using a hardware-in-the-loop (HIL) simulation platform and comparative analysis demonstrate that the HIO-based EMS effectively improves the transient operating conditions of the battery and fuel cell, extending their lifespan and enhancing system efficiency. Furthermore, the HIO-based EMS achieves a 95.20% level of hydrogen consumption compared to the MDDP-FSC-based EMS, validating its superiority. The MDDP-FSC-based EMS effectively avoids the extensive debugging efforts required to achieve a final state equilibrium, while providing valuable insights into the global optimal energy consumption potential of multi-energy source FCHETs. Full article