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A multi-period intuitionistic fuzzy consensus reaching model for group decision making problem in social network
A new intuitionistic fuzzy consensus reaching model is developed with multi-period public opinions and expert evaluation values in social network...
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A granularity data method for power frequency electric and electromagnetic fields forecasting based on T–S fuzzy model
The impact of electromagnetic radiation generated by signal transmission base stations and power stations to meet the needs of communication...
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A faster heuristic for the traveling salesman problem with drone
The Flying Sidekick Traveling Salesman Problem (FSTSP) consists of using one truck and one drone to perform deliveries to a set of customers. The...
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Improving the reliability of nanosatellite swarms by adopting blockchain technology
Satellite swarm networks have occupied a prominent position in many modern applications due to their low cost, simplicity of design, and flexibility....
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A proposed framework for supplier selection and order allocation using machine learning clustering and optimization techniques
The process of selecting the most suitable suppliers and allocating orders to them is critical in supply chain management. This research proposes a...
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TUMDOT–MUC: Data Collection and Processing of Multimodal Trajectories Collected by Aerial Drones
Currently available trajectory data sets undoubtedly provide valuable insights into traffic events, the behavior of road users and traffic flow...
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Improved randomized approaches to the location of a conservative hyperplane
This paper presents improved approaches to the treatment of combinatorial challenges associated with the search process for conservative cuts arising...
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Self-representation with adaptive loss minimization via doubly stochastic graph regularization for robust unsupervised feature selection
Unsupervised feature selection (UFS), which involves selecting representative features from unlabeled high-dimensional data, has attracted much...
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Siamese capsule gorilla troops network-based multimodal sentiment analysis for car reviews
Sentiment analysis of online car reviews is a significant process in natural language processing. Numerous car enthusiasts and influencers create...
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Extended ExpTODIM technique based on GRA for capability evaluation of real estate general contractors with hesitant triangular fuzzy information
The competition between real estate enterprises in the future is likely to be between supply chains, and strategic general contracting is an...
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An adaptive Q-learning based particle swarm optimization for multi-UAV path planning
In recent times, the path planning of unmanned aerial vehicles (UAVs) in 3D complex flight environments has become a hot topic in the field of UAV...
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A critical take on the role of random and local search-oriented components of modern computational intelligence-based optimization algorithms
The concept of computational intelligence (CI)-based optimization algorithms emerged in the early 1960s as a more practical approach to the...
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A performance comparison of deep learning and shallow machine learning in acoustic emission monitoring of aluminium alloy pulsed laser welding
The penetration depth is one of the important indicators in aluminium alloy laser welding, which is closely related to the welding quality. In situ...
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A machine learning-enhanced endpoint detection and response framework for fast and proactive defense against advanced cyber attacks
The risk of intelligent cyber-attacks is increasing as the number of endpoint devices surges and non-face-to-face services expand. As the damage...
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Multi-criteria decision-making using a complete ranking of generalized trapezoidal fuzzy numbers: modified results
Marimuthu and Mahapatra (Soft Comput 25:9859–9871, 2021) claimed that several methods are proposed in the literature to solve such multi-criteria...
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Uncertain queueing model with group arrivals
The main goal of mathematical modeling and analysis of queueing systems is to understand the dynamic behavior of the underlying processes, enabling...
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Quantum extremal learning
We propose a quantum algorithm for “extremal learning,” which is the process of finding the input to a hidden function that extremizes the function...
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A multi-population-based marine predators algorithm to train artificial neural network
Marine predators algorithm (MPA) is one of the recently proposed metaheuristic algorithms. In the MPA, position update mechanisms are implemented,...
