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26 articles for “fuzzy optimization”
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Representation-Theoretic Symmetry Reduction and Fuzzy-Grey Optimization of Modular Vibration Systems
Abstract: This paper presents a representation-theoretic framework for symmetry-aware vibration control in modular structural systems. Exploiting cyclic symmetry, the mass, damping, and stiffness operators are block-diagonalised into irreducible representations, reducing the full structural dynamics to a collection of lower-dimensional modal subsystems. This decomposition provides both computational efficiency and a rigorous mathematical description of symmetry-preserving dynamic behaviour. To account for imperfections arising in practical implementations, near-symmetry defects in stiffness and damping are …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 22–30 Read article
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Intuitionistic Fuzzy Hypergraph Laplacians and Dominating Transversals for Resilient Discrete Network Design
Abstract: This manuscript develops a discrete mathematical framework for resilience analysis on networks whose interactions are polyadic, uncertain, and partially conflicting. Classical graphs compress multi-way coordination into pairwise edges, while ordinary fuzzy graphs often ignore the non-membership information that becomes critical in emergency logistics, infrastructure interdependence, and cyberphysical coordination. We therefore formulate an intuitionistic fuzzy hypergraph in which each vertex hyperedge incidence carries membership, non-membership, and hesitation, and we construct a …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 2, 2026 · pp. 15–21 Read article
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Quasi-Sobol-Based Optimization and Sigmoid Fuzzy Logic for Efficient Task Clustering in Decentralized Edge-Cloud Architectures
Abstract: Decentralized edge-cloud systems face a lot of issues in efficient task clustering, resource allocation, and real-time decision-making. Conventional methods mostly fail to work well under dynamic workloads and uncertain conditions. This study intends to optimize task clustering through quasi-Sobol-based optimization and Sigmoid Fuzzy Logic for resource allocation, enhancing decision-making accuracy and achieving efficiency in the system at the edge-cloud environment. A hybrid technique that has incorporated optimization via Quasi-Sobol sequences …
Published in Trends in Machine design · Vol. 12, Issue 2, 2025 · pp. 9–18 Read article
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Optimization of Biohybrid Polymer Synthesis Using Fuzzy Inference Systems
Abstract: This investigation proposes a methodology to optimize biohybrid polymer synthesis using fuzzy inference systems (FIS). The study combines fuzzy logic principles with mathematical calculations for finding the best synthesis parameters to enhance the synthesis quality. This study consists on a sample about the use of FIS on optimisation of polymer synthesis, where they show the process of fuzzification, rule base creation, inference mechanism and defuzzification using the centroid method through …
Published in Journal of Polymer & Composites · Vol. 12, Issue 5, 2024 · pp. 36–47 Read article
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Multi-Objective Optimization of Carbon-Glass Fiber Polymer Drilling Process Based on Fuzzy Grey Entropy Weighing Method
Abstract: In recent years, the machining characteristics of hybrid fiber polymer composites have garnered significant research attention due to their growing industrial applications. This study specifically focuses on the drilling of hybrid carbon-glass fiber reinforced (CGFR) epoxy composites, fabricated using the hand layup technique. The key machining characteristics evaluated in this drilling process include surface roughness and circularity error. The influence of critical drilling process parameters, such as spindle speed, drill …
Published in Journal of Polymer & Composites · Vol. 13, Issue 6, 2025 · pp. 100–112 Read article
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Optimizing Sampling Techniques Using Fuzzy Set Theory: A Comprehensive Approach
Abstract: Sampling is a critical process in statistics, used to estimate population parameters without needing to examine the entire population. Traditional sampling methods, such as simple random sampling, stratified sampling, and cluster sampling, face limitations when applied to complex or heterogeneous populations with imprecise boundaries. These methods often fail to accurately represent populations with overlapping characteristics or missing data, resulting in sampling bias and reduced accuracy. To address these challenges, this …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 29–43 Read article
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An Innovative Fuzzy-Enhanced Black Widow Spider Optimization for Energy-Efficient Cluster Communication Through the Selection of the Ideal Cluster Head
Abstract: This paper presents a novel approach to enhance energy efficiency in cluster-based wireless sensor networks (WSNs) by integrating fuzzy logic with the black widow spider optimization (BWSO) algorithm. The focus of the suggested fuzzy-enhanced BWSO approach is on cluster head selection, which is essential for lowering energy consumption and enhancing network performance. The program uses fuzzy logic to assess a number of factors, including network density, node proximity, and energy …
Published in International Journal of Wireless Security and Networks · Vol. 2, Issue 2, 2024 · pp. 28–34 Read article
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Optimization of Surface Roughness and Material Removal Rate in Turning of Al-6061 Using Taguchi Methodology, Fuzzy Logic, and Measurement System Analysis
Abstract: The optimization of machining parameters please a crucial role in improving product quality and productivity in manufacturing processes. This study focuses on the turning of aluminium 6061 alloy, aiming to optimize two key performance measures: Surface Roughness and Material Removal Rate. An integrated approach combining to Taguchi methodology, fuzzy logic and measurement system analysis (MSA) is proposed to achieve this objective. Taguchi design of experiments using and L9 orthogonal array …
Published in International Journal of Machine Systems and Manufacturing Technology · Vol. 4, Issue 1, 2026 Read article
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Quasar: Quantum-Accelerated Sustainable Anomaly Recognition in Climate Systems
Abstract: Accurate detection of climate anomalies is vital for disaster alleviation and policy making in a sustainable manner, but customary detection methods face the challenges of computational inefficiency and physical inconsistency. In this study, we propose a novel approach called Quantum-Optimized Fuzzy Physics-Informed Neural Networks (QFuzzy-PINNs), which integrates quantum computing, fuzzy logic, and physics-informed deep learning. As a first step, we employ quantum annealing for conventional optimization to adjust multiple Gaussian …
Published in International Journal of Climate Conditions · Vol. 2, Issue 2, 2025 · pp. 18–27 Read article
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Spectral Intuitionistic Fuzzy Hypergraph Operators and Dominance Kernels for Resilient Discrete Network Design
Abstract: A new discrete-mathematical framework is developed for resilient network design on intuitionistic fuzzy hypergraphs, where uncertainty is explicitly represented through membership, non-membership, and hesitation degrees associated with both vertices and hyperedges. These three components are systematically integrated into an effective incidence operator that captures the underlying uncertain relationships within complex hypergraph structures. Based on this operator, both un-normalised and normalized Laplacian matrices are formulated to characterize the spectral properties and …
Published in Recent Trends in Mathematics · Vol. 3, Issue 2, 2026 · pp. 41–48 Read article
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Conceptualization of An Intelligent Decision Framework for Control Factors and Weld Quality Prediction
Abstract: To improve the robot's welding quality, control welding precision, optimize welding parameters, realize continuous welding quality database optimization, and increase welding defect detection, a fuzzy neural network-based intelligent decision-making system must be built. This study demonstrates how fuzzy control theory and BP neural networks may be used to identify welding issues and enhance process variables. The experimental findings indicate that, with seam classification accuracy close to 90%, enhancing welding parameters …
Published in Journal of Polymer & Composites · Vol. 11, Issue 6, 2023 · pp. 10–19 Read article
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Expanding Hicks Contraction Theory, Multi-Valued Mappings in Generalized b-Menger Spaces
Abstract: This paper extends the Hicks contraction theory to multi-valued mappings within generalized b-Manger spaces, a class of metric-like structures that accommodate more flexible distance functions. By introducing new definitions, such as generalized admissibility conditions and weak compatibility in the multivalued sense, we provide a comprehensive analysis of how these contractions behave in broader topological and metric contexts. Our approach systematically generalizes classical contraction principles by relaxing conventional constraints, thereby broadening …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 1–05 Read article
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Literature Review and Research Gaps in Power Quality Enhancement: From Conventional Methods to Intelligent Solutions
Abstract: Power quality (PQ) has become a critical concern in modern electrical power systems due to the rapid integration of renewable energy sources, proliferation of power electronic devices, and increasing sensitivity of loads. This paper presents a comprehensive literature review and research gap analysis of power quality enhancement techniques, ranging from conventional approaches to emerging intelligent solutions. Traditional methods, including passive filters, capacitor banks, and synchronous condensers, have been widely employed …
Published in International Journal of Electrical Machine Analysis and Design · Vol. 4, Issue 1, 2026 · pp. 38–80 Read article
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Fuzzy Mathematics in Decision-Making: A Quantitative Perspective
Abstract: Fuzzy mathematics plays an increasingly generalized role in decision-making, and thus, this paper details different types of fuzzy mathematics and highlights other possible alternatives alongside fuzzy methodologies. Fuzzy models offer a versatile and precise approach to assessing complex and uncertain situations using fuzzy sets, membership functions, linguistic variables, and aggregation methods. Through the lenses of time, cost, and quality, the project management case study illustrates how fuzzy logic effectively evaluates …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 6–12 Read article
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Study of Proximity Points and Fixed Points
Abstract: This paper explores the concepts of proximity points and fixed points, which are fundamental in mathematical analysis and nonlinear functional analysis. Fixed-point theorems play a crucial role in optimization, game theory, differential equations, and dynamic systems. Proximity points, an extension of fixed points, provide a more generalized approach, allowing near-coincidence rather than exact identity. The study discusses classical fixed-point theorems, such as Banach’s contraction principle, Brouwer’s fixed-point theorem, and Schauder’s …
Published in Recent Trends in Mathematics · Vol. 1, Issue 2, 2024 · pp. 28–31 Read article
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Identification and Evaluation of Safety Factors in Construction Industry Using Fuzzy Reasoning Technique
Abstract: Modern construction projects, characterized by their complexity and uniqueness, are inherently susceptible to various risks. These risks represent uncertain events that may arise during the project's life cycle, potentially influencing its objectives either positively or negatively. Positive risks are referred to as opportunities, while negative risks are identified as threats. To effectively harness these opportunities and mitigate threats, the implementation of Risk Management is essential. A novel theoretical framework known …
Published in Journal of Industrial Safety Engineering · Vol. 12, Issue 3, 2025 · pp. 7–12 Read article
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Advancements in Multiple-Input DC–DC Converters for Hybrid Renewable Energy Systems: Topologies, Control Strategies, and Applications
Abstract: Multiple-input DC to DC converters (MICs) are essential components in hybrid energy systems, enabling efficient management of diverse energy inputs from renewable sources such as solar photovoltaic (PV) panels and wind turbines. These converters facilitate the seamless integration of variable power outputs, addressing the intermittent nature of renewable energy through advanced power electronics. This paper provides a comprehensive review of the topologies, control strategies, and applications of MICs within renewable …
Published in Trends in Electrical Engineering · Vol. 15, Issue 2, 2025 · pp. 10–17 Read article
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Deep Reinforcement Learning-Based Intelligent Energy Management Strategy for Battery–Supercapacitor Hybrid Energy Storage Systems in Electric Vehicles
Abstract: As the number of EVs increases, smart solutions for energy management are needed that will optimize energy use, prolong battery life and boost vehicle performance. The application of conventional rule based and optimization-based Energy Management Strategies (EMS) for Battery–Supercapacitor Hybrid Energy Storage Systems (HESS) often leads to sub-optimal power management, supercapacitor mismatch and battery degradation when subjected to varying driving conditions. This study aims to design an intelligent energy management …
Published in International Journal of Advanced Control and System Engineering · Vol. 4, Issue 2, 2026 Read article
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A novel similarity measure for interval value picture fuzzy Environment and extended TOPSIS
Abstract: Correct decision-making is the most arduous task in our daily life. The decisions are hard to make in the multi-criteria decision-making (MCDM) problems due to ambiguous and unexpected information. In order to cope with such uncertainties in the data, a new decision-making approach has been developed using a newly defined similarity measure under the framework of interval-valued picture fuzzy set (IVPFS), as an extension of picture fuzzy sets (PFS). In …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 1, 2024 · pp. 1–10 Read article
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Implementing Machine Learning in Data Classification
Abstract: Data classification forms an essential aspect of artificial intelligence (AI) and soft computing, helping a great deal in the transformation of raw data into knowledge that forms the basis of numerous applications, such as fraud detection, medical diagnostics, and natural language processing. This study discusses the challenges and the state of the art in data classification, as far as scalability, noise handling, and feature selection optimization are concerned. It gives …
Published in International Journal of Data Structure Studies · Vol. 3, Issue 2, 2025 · pp. 15–22 Read article