Environmental projects have a high degree of uncertainty and risk of their implementation. In the process of assessing their effectiveness, it is necessary to take into account the interests of all the participants in...
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Numerous efforts in the literature are devoted to studying error bounds in optimization problems. The existence of local error bounds is closely related with constraint qualifications. It is well-known that some const...
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Job rotation can be defined as workers who move from one task to another which are classified based on various knowledge, skills, and abilities of individual employees. The current job rotation has not been effective ...
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Heart disease diagnosis using few measurements is a challenging an important task considering the increasing population. Artificial Neural Networks (ANNs) are promising mathematical architectures once the training is ...
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Heart disease diagnosis using few measurements is a challenging an important task considering the increasing population. Artificial Neural Networks (ANNs) are promising mathematical architectures once the training is performed in an elegant manner to avoid theoretical challenges related to high nonlinearity, nonconvexity using few input variables to ensure generalization capability. This study shows the impact of the piecewise linear approximation of nonlinear functions in ANN architecture and training problem to benefit from the mixed integer linear problem formulation for the simultaneous input selection and training to obtain mixed integer programming based ANN (MIP-ANN). Proposed formulation is further tailored through linking constraints to remove the connections from the eliminated inputs to favor parameter identifiability. A publicly available dataset is considered as a case study of whose results are also compared to traditional ANN with all inputs (FC-ANN) and a relatively more straightforward but common input selection method (SKB-ANN). The results provide a comparable performance despite significant reduction in the input space in addition to significant computational and theoretical advantages thanks to advanced formulation.
This paper proposes an intelligent obstacle avoidance method in unmanned driving. This method first establishes a simplified model for the obstacle avoidance problem in unmanned driving, and constrains the car from ki...
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Traffic congestion is a problem in large cities. It has many negative consequences for the economy, the environment and human health. Proper adjustment of the traffic light settings in urban environments is the main m...
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The sampling procedures for inspection by variables with the rate of the non-conforming product under the assumption that the product quality characteristics are subject to the normal distribution is discussed. This p...
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Train rescheduling is a nonlinear optimization problem with multiple constraints. In the view of the theoretical methods and the actual application, the train intelligent rescheduling model is set up according to its ...
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Sky wave over-the-horizon radar (OTHR) need carry out complex and diversified tasks with wide detection region. In order to improve overall detection effectiveness, detection resource scheduling of OTHR should be conc...
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Unlike real-world filmmaking, the camera track in 3D animated films is more complicated. The location and shooting angle of the virtual camera need to be more accurately computed to achieve the correct delivery of inf...
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