This paper investigates the delay-dependent stability problem of continuous neural networks with a bounded time-varying delay via Lyapunov–Krasovskii functional (LKF) method. This paper focuses on ...reducing the conservatism of stability criteria by estimating the derivative of the LKF more accurately. Firstly, based on several zero-value equalities, a generalized free-weighting-matrix (GFWM) approach is developed for estimating the single integral term. It is also theoretically proved that the GFWM approach is less conservative than the existing methods commonly used for the same task. Then, the GFWM approach is applied to investigate the stability of delayed neural networks, and several stability criteria are derived. Finally, three numerical examples are given to verify the advantages of the proposed criteria.
Sustainable manufacturing practices and the circular economy have recently received significant attention in academia and within industries to improve supply chain practices. Manufacturing industries ...have started adopting sustainable manufacturing practices and a circular economy in their supply chain to mitigate environmental concerns, as sustainable manufacturing practices and a circular economy result in the reduction of waste generation and energy and material usage. The leather industry, in spite of it contributing remarkably to a country's economic growth and stability, does not bear a good image because of its role in polluting the environment. Therefore, the leather industries of Bangladesh are trying to implement sustainable manufacturing practices as a part of undertaking green supply chain initiatives to remedy their image with the buyer and to comply with government rules and regulations. The main contribution of this study is to assess, prioritize and rank the drivers of sustainable manufacturing practices in the leather industries of Bangladesh. We have used graph theory and a matrix approach to examine the drivers. The results show that knowledge of the circular economy is paramount to implementing sustainable manufacturing practices in the leather industry of Bangladesh. This study will assist managers of leather companies to formulate strategies for the optimum utilization of available resources, as well as for the reduction of waste in the context of the circular economy.
•To handle the uncertainty decision problems in incomplete hybrid data, a generalized three-way neighborhood decision model is proposed by distributing the interval-valued loss function to each ...object and averaging the interval-valued loss functions of all objects in the data-driven neighborhood class.•A matrix-based approach for representing three-way regions in the generalized three-way neighborhood decision model is presented by introducing the matrix forms of related concepts and the matrix operators.•An efficient framework for dynamically updating the three-way regions is provided when objects and attributes increase simultaneously.•An incremental algorithm based on matrix is designed for maintaining the three-way regions.•Experimental results demonstrate that the proposed incremental algorithm has an advantage in improving the computational performance.
The theory of three-way decisions, as a powerful methodology of granular computing, has been widely used in making decision under uncertainty environments. Decision tasks in incomplete hybrid data including heterogeneous and missing features are of abundance in realistic situations. To deal with these tasks, some work based on three-way decisions has been investigated. However, the losses used for evaluating objects are precise real numbers, which makes these decision models have some limitations in applications when there exist missing values in incomplete hybrid data. Thus, this paper constructs a generalized three-way neighborhood decision model by assigning the interval-valued loss function to each object and further adopting an average strategy to integrate the interval-valued loss functions of objects in each data-driven neighborhood class. Moreover, considering that the objects and attributes of incomplete hybrid data will simultaneously change over time, this paper also provides an efficient framework to dynamically maintain three-way regions of the proposed model. An approach based on matrix to compute the three-way regions is first presented by introducing the matrix operations and the matrix forms of related concepts. Then, with the simultaneous variation of objects and attributes, the matrix-based incremental mechanism and algorithm are proposed for updating the three-way regions, respectively. Experimental results on nine datasets indicate that the proposed incremental algorithm can effectively improve the computational performance for evolving data in comparison with the static algorithm.
The data collected from the real world are diverse and include categorical data, numerical data, incomplete data and noisy data. In addition, many real data sets may dynamically vary, and dynamic ...data display characteristics with multi-dimensional variations. However, for mixed incomplete data systems, most of the existing incremental methods only work well with single-dimensional dynamic data sets and are not suitable for processing specific multi-dimensional variations of objects and attributes. In this paper, we focus on researching dynamic approaches to efficiently update three-way regions based on the simultaneous variations of the object set and the attribute set in an incomplete neighborhood decision system (INDS). First, considering the complexity of data, we utilize matrix approaches to calculate three-way regions of the INDS based on a proposed neighborhood tolerance relation. Then, under the simultaneous addition of the object set and the attribute set in the INDS, we research incremental mechanisms based on the matrix to obtain three-way regions from previous knowledge. Subsequently, an incremental algorithm for updating three-way regions is proposed when the object set and the attribute set are simultaneously added to the INDS. Finally, the results of a series of experiments and comparisons based on UCI data sets show that the performance of the proposed incremental algorithm is much better than that of the traditional static algorithm, the integrated single-dimensional incremental algorithm and the single-level combined incremental algorithm.
This paper investigates the exponential synchronization problem of memristive recurrent neural networks (MRNNs). A novel approach, switching matrix approach, is considered to study synchronization of ...MRNNs for the first time. All the matrices in the constructed Lyapunov–Krasovskii functional (LKF) are switching according to different switching rules. Based on the switching matrix approach, a new synchronization criterion is established in the form of linear matrix inequalities (LMIs). Compared with some existing methods, the switching matrix approach is more flexible and can improve the synchronization performance with low control cost. Finally, numerical simulations are provided to show the effectiveness and advantages of the proposed results.
This note is concerned with the stability analysis of linear discrete-time system with a time-varying delay. A generalized free-weighting-matrix (GFWM) approach is proposed to estimate summation ...terms in the forward difference of Lyapunov functional, and theoretical study shows that the GFWM approach encompasses several frequently used estimation approaches as special cases. Moreover, an augmented Lyapunov functional with a delay-product type term is constructed to take into account delay changing information. As a result, the proposed GFWM approach, together with the augmented Lyapunov functional, leads to a less conservative delay-variation-dependent stability criterion. Finally, numerical examples are given to illustrate the advantages of the proposed criterion.
Wireless sensor network (WSN) is a group of a huge number of low price, low control, and self-organizing specialized sensor nodes. WSN is very much vulnerable to different types of physical attacks ...due to limited resource capacity and screened to external atmosphere for circulating data. The node capture attack is one of the major attacks in WSN in which the intruder physically captures the node and remove the secret information from the node’s memory. We propose a Fruit Fly Optimization Algorithm (FFOA) that is based on multiple objectives node capture attack algorithm which consists of several objectives: maximum node contribution, maximum key contribution, and least resource expenses to discover optimal nodes. It will influence an inclusive tool to demolish maximum part of the network along with effective cost and maximum attacking efficiency. The simulation result illustrates that FFOA obtains a maximum fraction of compromised traffic, lower attacking rounds, and lower energy cost as compared with Genetic Algorithm (GA) and other node capture attack algorithms. Therefore, FFOA gives maximum attacking efficiency than GA and other algorithms by capturing minimum nodes that compromise the whole network.
•Barriers for AM adoption are categorized based on TOE and IRT principles.•High investment cost and lack of knowledge are major barriers.•Integrated approach comprising of FDM, BWM and GTMA has been ...used.•Self- assessment framework for evaluating barriers intensity has been proposed.
Additive manufacturing (AM) is a revolutionary technological advancement that has the potential to contribute to sustainability in operations. The environmental benefits offered by AM have motivated firmsto the adoption of this technology. However, the real-world examples of successful applications of AM are limited. This study aims to explore and prioritise the challenges faced during the adoption of AM to achieve circular economy goals. The fuzzy Delphi method is used to finalise the barriers with the help of experts’ opinions. Then, using the Best Worst Method, the prioritisation of barriers has been done. Finally, the Graph Theory Matrix approach is used for the quantification of barriers’ intensity for a case company in the Indian automotive manufacturing industry.The study uses TOE (Technology, Organisation, Environment) theory and Innovation Resistance theory in the context of AM adoptionbarriers to achieving circular economy goals. This study will help decision-makers to tackle their ambivalence towards the feasibility of implementing AM to achieve sustainability. The proposed self-assessment framework will help in evaluating barriers' intensity while implementing AM. Insights from the study will also be useful for developing effective strategies for AM.
The thermal entanglement in a mixed spin-(1/2, 5/2, 1/2) Ising–Heisenberg branched chain is investigated by employing negativity as entanglement measurement. Using transfer-matrix approach, the ...negativity is calculated numerically both near and at a quantum phase transition point. We establish the relationship between negativity and quantum phase transition. It is found that whether negativity can be used to detect quantum phase transition point depends on the typical thermal energy, and we show the range of temperature at which negativity can be used to signal each ground-state transition. In addition, the thermal stability of negativity is closely related to energy gap in the system. It is worth noting that the negativity exhibits distinct behavior between quantum and classical phases. Negativity decreases with the increase of temperature in the quantum phase, while it exhibits a ”regrowth” behavior in the classical phases.
•We study the thermal entanglement in a mixed spin Ising–Heisenberg branched chain.•The relationship between energy gap and quantum phase transition is discussed.•Quantum phase transition can be detected and signaled by thermal negativity.
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