Ranking challenges, risks and threats using Fuzzy Inference System

Decision Making Applications in Management and Engineering, Год журнала: 2023, Номер 6(2), С. 933 - 947

Опубликована: Сен. 4, 2023

This paper presents a Fuzzy Inference System (FIS) designed to comprehensively assess challenges, risks, and threats. In the realm of security defense, defining these elements is inherently uncertain complex. The addresses this challenge by integrating fuzzy logic into model. As pivotal instrument for decision-making, model not only facilitates precise identification threats but also provides vital support strategic doctrinal document development process. methodology proves instrumental in reconciling divergent perspectives, aligning theoretical intricacies with practical applications. By effectively capturing nuanced interplay between variables, offers dynamic framework that enhances accuracy efficiency security-related decision-making.

Язык: Английский

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Evaluation of organizational culture in companies for fostering a digital innovation using q-rung picture fuzzy based decision-making model

Advanced Engineering Informatics, Год журнала: 2023, Номер 58, С. 102191 - 102191

Опубликована: Сен. 24, 2023

Developing a comprehensive data-driven strategy for evaluating the organisational culture in companies to foster digital innovation involves multi-criteria decision-making (MCDM) problem. This needs consider various characteristics that influence success, assign significance weights each characteristic, and recognise distinct cultures may excel different aspects necessitates proper handling of data variations. Hence, provide organisations seeking align cultural practises with objectives valuable insights, this study aims develop an MCDM model benchmarking innovation. The decision matrix is formulated based on intersection evaluation list companies. developed two phases. Firstly, new weighting model, q-rung picture fuzzy-weighted zero-inconsistency (q-RPFWZIC), assessing under fuzzy sets environment. Secondly, simple additive (SAW) using extracted characteristics. results indicate characteristic C6 (corporate entrepreneurship) has highest weight, value 0.161, while C3 (employee participation, agility organizational structures) C7 (digital awareness necessity innovations) lowest weight 0.088. Company A2 secures top rank score 0.911, satisfying eight characteristics, whereas company A7 holds last order, only one obtaining 0.101. In evaluation, several scenarios were considered sensitivity analysis test 100% increment values validate reliability results.

Язык: Английский

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Evaluating 3D-Printed Polylactic Acid (PLA)-Reinforced Materials: Mechanical Performance and Chemical Stability in Concrete Mediums

Applied Sciences, Год журнала: 2025, Номер 15(4), С. 2165 - 2165

Опубликована: Фев. 18, 2025

The optimization and evaluation of 3D-printed polylactic acid (PLA) materials for reinforcing concrete elements present a promising avenue advancing sustainable construction methods. This study addresses the challenges associated with PLA’s dual nature—biodegradable yet mechanically limited long-term applications—while leveraging its potential to enhance reinforcement. research identifies gaps in understanding mechanical chemical behavior alkaline environments, particularly interactions matrices. To bridge this gap, four distinct PLA variants (high-impact PLA, engineering electrical ESD gypsum PLA) ABS (acrylonitrile butadiene styrene) were subjected dissolution tests NaOH solutions (pH 12 12.55) under three-point bending using digital image correlation (DIC) technology. Test specimens prepared optimized 3D printing strategies ensure structural consistency embedded beams analyze their reinforcement potential. Force–displacement data GOM ARAMIS measurements revealed significant differences responses, peak loads ranging from 0.812 kN 1.021 (electrical PLA). Notably, exhibited post-failure load-bearing capacity, highlighting capability. Chemical material-specific degradation patterns, high-impact Gypsum showing accelerated surface changes precipitation phenomena. Observations indicated white crystalline precipitates, likely lime (calcium hydroxide—Ca(OH)2), residue (sodium hydroxide—NaOH), or material-derived residues formed on near elements, suggesting interactions. These findings underline critical role material selection achieving effective PLA–concrete integration. While environmental sustainability aligns industry goals, reliability exposure remains challenge. concludes that demonstrates highest application reinforced concrete, provided stability is managed, as value (1.021 kN) showed 25.7% higher capacity than (0.812 did not lose any tests. work advances alternative construction, offering insights future innovations applications.

Язык: Английский

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A Particle Swarm Optimization-Based Ensemble Broad Learning System for Intelligent Fault Diagnosis in Safety-Critical Energy Systems with High-Dimensional Small Samples

Mathematics, Год журнала: 2025, Номер 13(5), С. 797 - 797

Опубликована: Фев. 27, 2025

Intelligent fault diagnosis (IFD) plays a crucial role in reducing maintenance costs and enhancing the reliability of safety-critical energy systems (SCESs). In recent years, deep learning-based IFD methods have achieved high accuracy extracting implicit higher-order correlations between features. However, excessive long training time learning models conflicts with requirements real-time analysis for IFD, hindering their further application practical industrial environments. To address aforementioned challenge, this paper proposes an innovative method SCES that combines particle swarm optimization (PSO) algorithm ensemble broad system (EBLS). Specifically, (BLS), known its low complexity classification accuracy, is adopted as alternative to SCES. Furthermore, EBLS designed enhance model stability high-dimensional small samples by incorporating random forest (RF) strategy into traditional BLS framework. order reduce computational cost EBLS, which constrained selection hyperparameters, PSO employed optimize hyperparameters EBLS. Finally, validated through simulated data from complex nuclear power plant (NPP). Numerical experiments reveal proposed significantly improved diagnostic efficiency while maintaining accuracy. summary, approach shows great promise boosting capabilities

Язык: Английский

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Mathematical Modeling of the Rail Track Superstructure–Subgrade System

Geotechnics, Год журнала: 2025, Номер 5(1), С. 20 - 20

Опубликована: Март 16, 2025

The “rail track superstructure–subgrade” system is a sophisticated engineering structure critical in ensuring safe and efficient train operations. Its analysis design rely on mathematical modeling to capture the interactions between components effects of both static dynamic loads. This paper offers detailed review contemporary approaches, including discrete, continuous, hybrid models. research’s key contribution thorough comparison five primary methodologies: (i) quasi-static analytical calculations, (ii) multibody dynamics (MBD) models, (iii iv) finite element method (FEM) (v) wave propagation-based Future research directions could focus developing models that integrate MBD FEM enhance moving load predictions, leveraging machine learning for parameter calibration using experimental data, investigating nonlinear rheological behavior ballast subgrade long-term deformation, applying propagation techniques model vibration transmission evaluate its impact infrastructure.

Язык: Английский

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A metaheuristic optimization framework inspired by virus mutations and its ability to optimize the structural design of 2D and 3D steel frames compared to other methods

Results in Engineering, Год журнала: 2025, Номер unknown, С. 105020 - 105020

Опубликована: Апрель 1, 2025

Язык: Английский

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A bi-objective model for location, dispatch and relocation of ambulances with a revision of dispatch policies

Kybernetes, Год журнала: 2024, Номер unknown

Опубликована: Апрель 23, 2024

Purpose Untimely responses to emergency situations in urban areas contribute a rising mortality rate and impact society's primary capital. The efficient dispatch relocation of ambulances pose operational momentary challenges, necessitating an optimal policy based on the system's real-time status. While previous studies have addressed these concerns, limited attention has been given allocation technicians respond situation minimize overall system costs. Design/methodology/approach In this paper, bi-objective mathematical model is proposed maximize coverage enable flexible movement across bases for location, ambulances. Ambulances involves two key decisions: (1) allocating after completing services (2) deciding change current ambulance location among existing potentially improve response times future emergencies. also considers varying capabilities proper situations. Findings Augmented Epsilon-Constrained (AEC) method employed solve small-sized problem. Due NP-Hardness model, NSGA-II MOPSO metaheuristic algorithms are utilized obtain solutions large-sized problems. findings demonstrate superiority algorithm. Practical implications This study can be useful medical centers healthcare companies providing more effective by sending Originality/value study, two-objective developed solved using AEC as well algorithms. encompasses three types decision-making: Allocating their service, relocate enhance emergencies (3) considering diverse abilities accurate

Язык: Английский

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Metaheuristic Algorithms for the Optimization of Integrated Production Scheduling and Vehicle Routing Problems in Supply Chains

Tehnicki vjesnik - Technical Gazette, Год журнала: 2024, Номер 31(3)

Опубликована: Апрель 23, 2024

This paper examines the challenge of integrated production and distribution, aiming to deliver products customers precisely on time.Customers, situated within transportation network, have predefined requirements regarding demand volume time frames.In first phase (F1), problem planning allocation resources is presented as FJSP, while second (F2) addresses vehicle routing CVRPTW.The phase, F1, aims optimize manufacturing processes by appropriately scheduling tasks maximize productivity minimize task execution machines.Phase 2, F2, encompasses process distribution customers, seeking number vehicles, delivery time, overall distance travelled.As both problems are among most challenging in combinatorial optimization, integrating these phases into a single supply chain system poses significant problem-solving.A mathematical formulation has been developed include production, well routing, obtain an optimal solution problem.The input data used observed case study represent real phases, forming one system.Experimental results support applied methodology.

Язык: Английский

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Accelerate Assessment Calculations for Quadratic Assignment Problem Solution

Опубликована: Янв. 29, 2024

The Quadratic Assignment Problem (QAP) is widely recognized as an important combinatorial optimization problem. QAP finds extensive applications in practical scenarios such facility placement, computer manufacturing, communication networks, and other areas. It solves real-world challenges by optimizing resource allocation a way that minimizes costs or distances. essence of the proposed approach systematic enumeration possible permutations elements using next lexicographical permutation heap's methods. Rather than relying on random heuristic-based initialization, we generate predictable sequence. Moreover, this study proposes efficient calculation selectively calculates only changes resulting from adjustment permutations, thereby reducing need to re-evaluate entire cost function for each speeding up search optimal solutions. In addition, employ brute force algorithm, which evaluates all permutation, illustrative implementation C++ program QAP. demonstrates improved computational efficiency, reduces space, opens avenues further exploration use technologies problems larger problem instances.

Язык: Английский

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Design and optimization of two-stage controller for three-phase multi-converter/multi-machine electric vehicle

Open Engineering, Год журнала: 2024, Номер 14(1)

Опубликована: Янв. 1, 2024

Abstract Electric vehicles (EVs) cut greenhouse gas emissions and our use of non-renewable resources, making them more attractive. EVs have lower fuel maintenance expenses than internal combustion engine automobiles. This study proposes a multi-converter/Multi‒Machine system with two induction motors (IM) that drive pure EV’s rear wheels. EV two-stage controllers using simple Adaline neural network (NN) regulate Field-Oriented three-phase IM. To control IM speed, the first controller level is hybrid proportional–integral (PI) robust integral sign error (RISE) controller. Injection torque controlled by PI‒adaline NN in second step. The improves performance. Multi-Verse Optimization algorithm found ideal RISE parameter to improve A plug-in linear speed Electronic Differential Controller (EDC). It uses driver’s reference steering angle set each driving wheel’s speed. EDC adjusts wheel speeds enhance traction stability during cornering, accelerating, decelerating. Utilizing this information, can effectively distribute power wheels, thereby enhancing vehicle handling overall Three distinct road scenarios designated route topology been used act demonstrate resistive forces affected while it was traveling down road. By Matlab (Simulink), roadworthiness efficiency will be evaluated.

Язык: Английский

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