Personalized tourist route planning (TRP) and navigation are online or real-time applications whose mathematical modeling leads to complex optimization problems. These problems are usually formulated with mathematical...
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Personalized tourist route planning (TRP) and navigation are online or real-time applications whose mathematical modeling leads to complex optimization problems. These problems are usually formulated with mathematical programming and can be described as NP hard problems. Moreover, the state-of-the-art (SOA) path search algorithms do not perform efficiently in solving multi-objective optimization (MO) problems making them inappropriate for real-time processing. To address the above limitations and the need for online processing, a swarm intelligence graph-based pathfinding algorithm (SIGPA) for MO route planning was developed. SIGPA generates a population whose individuals move in a greedy approach based on A* algorithm to search the solution space from different directions. It can be used to find an optimal path for every graph-based problem under various objectives. To test SIGPA, a generic MOTRP formulation is proposed. A generic TRP formulation remains a challenge since it has not been studied thoroughly in the literature. To this end, a novel mixed binary quadratic programming model is proposed for generating personalized TRP based on multi-objective criteria and user preferences, supporting, also, electric vehicles or sensitive social groups in outdoor cultural environments. The model targets to optimize the route under various factors that the user can choose, such as travelled distance, smoothness of route without multiple deviations, safety and cultural interest. The proposed model was compared to five SOA models for addressing TRP problems in 120 various scenarios solved with CPLEX solver and SIGPA. SIGPA was also tested in real scenarios with A* algorithm. The results proved the effectiveness of our model in terms of optimality but also the efficiency of SIGPA in terms of computing time. The convergence and the fitness landscape analysis showed that SIGPA achieved quality solutions with stable convergence.
The frequent occurrence of financial fraud caused by listed companies has seriously hindered the healthy development of the capital market. Existing studies usually analyze financial fraud through the effectiveness of...
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The frequent occurrence of financial fraud caused by listed companies has seriously hindered the healthy development of the capital market. Existing studies usually analyze financial fraud through the effectiveness of audit opinion or the correlation between auditor change rate and financial fraud, ignoring the relationship between different participants. By using the audit relationships among corporations, audit firms and auditors, this paper constructs an audit information knowledge graph and proposes a knowledge graph reasoning framework based on the Sub Feature Extraction method to detect potential fraud corporations. In the process of analyzing the audit data of 376 companies in the China Growth Enterprises Market from 2013 to 2019, it is found that potential fraud corporations can be well identified by searching from the known fraud corporations using searched paths. In addition, we find two new audit features of financial fraud corporations which are respectively related to abnormal audit opinions issued by auditors and abnormal associations of audit firms. They can help regulators more effectively find the potential financial fraud corporations that need to be supervised.
With the continuous development of UAV technology,autonomous path planning methods suitable for UAVs are also *** complex environments,UAVs not only need to consider the dynamics and time constraints,but also find the...
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ISBN:
(纸本)9781665448109
With the continuous development of UAV technology,autonomous path planning methods suitable for UAVs are also *** complex environments,UAVs not only need to consider the dynamics and time constraints,but also find the best and collision-free *** many researchers have conducted research on UAV path planning,there is a lack of comprehensive investigation and intuitive display of UAV path planning in a three-dimensional complex unknown *** article comprehensively analysis the path search algorithm and trajectory optimization method for UAVs in a three-dimensional environment,classifies them and compares them for each category,analyses the advantages and disadvantages of these methods.
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