Multiview fuzzy clustering (MVFC) has gained widespread adoption owing to its inherent flexibility in handling ambiguous data. The proliferation of privatization devices has driven the emergence of new challenge in MV...
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Abstract: In this paper, motivated by previous related works on a kind of quantum local adiabatic evolution, we mainly study the circuit model of its corresponding quantum global adiabatic search algorithm, in which t...
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In recent years, as people’s living standards have improved and consumption concepts have been transformed, the demand for purchasing consumer electronics online has continued to grow, further stimulating the develop...
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In recent years, as people’s living standards have improved and consumption concepts have been transformed, the demand for purchasing consumer electronics online has continued to grow, further stimulating the development of the logistics industry. Consequently, how to deliver consumer electronics to households at minimal cost has become a crucial factor that limits the development of the consumer technology industry. To tackle this problem, this paper studies the task assignment problem for multiple initially dispersed UAVs to deliver products to target locations while minimizing their total operation time. Each UAV can continuously provide delivery services to multiple target locations within its limited loading capacity and operation time. To solve this problem, we propose several hybrid multipopulation genetic algorithms. First, a novel crossover operator for the genetic algorithms is designed, through which a single parent chromosome can generate offspring individually. Second, two mutation mechanisms are performed to increase gene diversity. Third, multiple local search strategies are employed to enhance the populations’ fitness during each iteration of evolution. An improved 2-opt local search strategy is applied to optimize individual chromosomes when their similarity with the current best chromosome falls below a prescribed threshold. Alternatively, local search strategies are utilized for 1-opt, 2h-opt and interchange processes. Combining local search strategies, genetic operators, and the multi-population mechanism leads to several hybrid multi-population genetic algorithms. Numerical simulations and experimental tests demonstrate that the hybrid multi-population genetic algorithm, integrated with the improved 2-opt and 1-opt local search strategies, exhibits superior performance among the designed hybrid genetic algorithms, the minimum marginal cost algorithm (MMA), and the existing popular Co-evolutionary Multi-population Genetic Algorithm (CMGA). In exp
作者：
Xu, JieZhou, JiantaoCollege of Computer Science
Engineering Research Center of Ecological Big Data Ministry of Education National and Local Joint Engineering Research Center of Mongolian Intelligent Information Processing Technology Inner Mongolia Cloud Computing and Service Software Engineering Laboratory Inner Mongolia Social Computing and Data Processing Key Laboratory Inner Mongolia Discipline Inspection and Supervision Big Data Key Laboratory Inner Mongolia Big Data Analysis Technology Engineering Laboratory Inner Mongolia University Hohhot China
Anomaly detection aims to find outliers data that do not conform to expected behaviors in a specific scenario, which is indispensable and critical in current safety environments related studies. However, when performi...
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Automatically solving math word problems,which involves comprehension,cognition,and reasoning,is a crucial issue in artificial intelligence *** math word problem solvers mainly work on word-level relationship extracti...
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Automatically solving math word problems,which involves comprehension,cognition,and reasoning,is a crucial issue in artificial intelligence *** math word problem solvers mainly work on word-level relationship extraction and the generation of expression solutions while lacking consideration of the clause-level *** this end,inspired by the theory of two levels of process in comprehension,we propose a novel clause-level relationship-aware math solver(CLRSolver)to mimic the process of human comprehension from lower level to higher ***,in the lower-level processes,we split problems into clauses according to their natural division and learn their *** the higher-level processes,following human′s multi-view understanding of clause-level relationships,we first apply a CNN-based module to learn the dependency relationships between clauses from word relevance in a local ***,we propose two novel relationship-aware mechanisms to learn dependency relationships from the clause semantics in a global ***,we enhance the representation of clauses based on the learned clause-level dependency *** expression generation,we develop a tree-based decoder to generate the mathematical *** conduct extensive experiments on two datasets,where the results demonstrate the superiority of our framework.
Knowledge Graph (KG) is an essential research direction that involves storing and managing knowledge data, but its incompleteness and sparsity hinder its development in various applications. Knowledge Graph Reasoning ...
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Multiphase flows are of great importance for the sustainable utilization of geological resources and ecological protection. Numerical simulation, as a general and powerful approach for multiphase flow modeling, faces ...
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Reinforcement learning (RL) has made great success in recent years. Generally, the learning process requires a huge amount of interaction with the environment before an agent can achieve acceptable performance. This m...
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Neuromorphic computing,inspired by the human brain,uses memristor devices for complex *** studies show that self-organizing random nanowires can implement neuromorphic information processing,enabling data *** paper pr...
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Neuromorphic computing,inspired by the human brain,uses memristor devices for complex *** studies show that self-organizing random nanowires can implement neuromorphic information processing,enabling data *** paper presents a model based on these nanowire networks,with an improved conductance variation *** suggest using these networks for temporal information processing via a reservoir computing scheme and propose an efficient data encoding method using voltage *** nanowire network layer generates dynamic behaviors for pulse voltages,allowing time series prediction *** experiment uses a double stochastic nanowire network architecture for processing multiple input signals,outperforming traditional reservoir computing in terms of fewer nodes,enriched dynamics and improved prediction *** results confirm the high accuracy of this architecture on multiple real-time series datasets,making neuromorphic nanowire networks promising for physical implementation of reservoir computing.
The equipment management informatization and intelligentization in railway passenger stations is a significant component of the construction of intelligent stations. The current equipment management of railway passeng...
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