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Vector-based uncertain ordered density weighted averaging: a family of incentive-oriented aggregation operators
Incentive is a common phenomenon in the process of decision management. It is important and necessary to integrate incentive requirement into the decision-making process. To this problem, the paper proposed a ...
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Addressing the traveling salesperson problem with frequency fitness assignment and hybrid algorithms
The traveling salesperson problem (TSP) is one of the most iconic hard optimization tasks. With frequency fitness assignment (FFA), a new approach to optimization has recently been proposed: instead of directi...
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An enhanced teaching–learning-based optimization for the flexible job shop scheduling problem considering worker behaviours
In actual workshop scheduling, processing time is influenced by worker behaviours, such as learning, forgetting, fatigue and recovery. However, in the traditional workshop scheduling considering workers, these...
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Fuzzy nominal sets
In this paper, we use two approaches to define the concept of fuzzy nominal sets: classic and universal algebraic. We see that the fuzzy nominal sets obtained using the universal algebraic approach (so-called ...
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A multiobjective multiperiod portfolio selection approach with different investor attitudes under an uncertain environment
Though there are several studies on uncertain single-period portfolio selection, the uncertain multiperiod portfolio selection literature is still in an exploration phase. Besides, the effects and influences o...
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A revolutionary RPL-based IoT routing protocol for monitoring building structural health in smart city domain utilizing equilibrium optimizer algorithm
The Internet of Things (IoT) has been the subject of recent studies and is expected to be extremely important to the future growth of the Internet. The essential component of the IoT is the low-power and lossy...
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A generalization of \(k\times j\) -rough Heyting algebras
A \(k\times j\) k × j ...
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An artificial bee colony algorithm for the minimum edge-dilation K-center problem
This paper studies the minimum edge-dilation K-center (MEDKC) problem for edge-weighted, undirected and connected graphs. This problem which is $$\mat...
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Optimal analysis and design of large-scale problems using a Modified Adolescent Identity Search Algorithm
This research uses a new method called the Modified Adolescent Identity Search Algorithm (MAISA) to solve optimization problems. The identity of a teenager is a different combination of thoughts, beliefs, and ...
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New characterizations of partial orders induced by a class of non-divisible t-norms
In this article, we deal with the algebraic structures of the partial orders induced by non-divisible t-norms. We first give a condition for the partial orders induced by non-divisible t-norms being a meet sem...
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Open AccessDesign of Human–Computer Interaction Gesture Recognition System Based on a Flexible Biosensor
The continuous development of high-speed Internet technology has made the application of robots increasingly widespread. Current robots and human–computer interaction systems mostly use rigid materials, such a...
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Open AccessStrong s-box construction approach based on Josephus problem
There are two basic requirements for symmetric encryption algorithms. The first of these is diffusion. The second and most important is confusion. In these algorithms, this requirement is usually met by s-box ...
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Open AccessOn join-complete implication algebras
In this paper, first, we consider an algebra that has a binary operation and a join of arbitrary nonempty subset. A lattice implication algebra is a lattice with a binary operation, which has a join and a meet...
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Generating fuzzy sets using rearranged nested family and the mathematical formula in decomposition theorem
The purpose of this paper is to propose a mechanical procedure to generate fuzzy data from the observed real number data. The observed data may be imprecise owing to some unexpected situation. In this case, th...
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Open AccessBipolar Neutrosophic Dombi-Based Heronian Mean Operators and Their Application in Multi-criteria Decision-Making Problems
Dombi operations based on the Dombi t-norm (TN) and t-conorm (TCN) have the advantage in terms of operational parameter flexibility in dealing with varying degrees of uncertainty and aggregation requirements. ...
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A greedy post-processing strategy for multi-objective performance optimization of general single-server finite queueing networks
Several real-life problems are comprised of finite single-server acyclic queueing networks. The performance optimization of these queueing networks has been the subject of several studies. The present study ex...
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Open AccessPredicting the potential toxicity of the metal oxide nanoparticles using machine learning algorithms
Over the years, machine learning (ML) algorithms have proven their ability to make reliable predictions of the toxicity of metal oxide nanoparticles. This paper proposed a predictive ML model of the potential ...
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Intrusion detection system and fuzzy ant colony optimization based secured routing in wireless sensor networks
Recent advances in wireless sensor networks (WSNs) have brought the sensor based monitoring developments to the surface in many applications. In such a scenario, the security of communication is a major challe...
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Open AccessSSO-CCNN: A Correlation-Based Optimized Deep CNN for Brain Tumor Classification Using Sampled PGGAN
Recently, new advancements in technologies have promoted the classification of brain tumors at the early stages to reduce mortality and disease severity. Hence, there is a need for an automatic classification ...
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Multi-objective meta-heuristics to optimize end-of-life laptop remanufacturing decisions under quality grading of returned parts
Research on multi-objective discrete optimization of Waste Electrical and Electronic Equipment (WEEE) remanufacturing remains under-studied in the literature. Remanufacturing laptops to extend their useful lif...
