in arid and semi-arid environments, groundwater plays a significant role in the ecosystem. in the last decades, groundwater levels have decreased due to the increasing demand for water, weak irrigation management and soil damage. for the effective management of groundwater, it is important to model and predict fluctuations in groundwater levels. in this study, groundwater table in kashan plain ...

We describe a quantum algorithm that solves combinatorial optimization problems by quantum simulation of a classical simulated annealing process. Our algorithm exploits quantum walks and the quantum Zeno effect induced by evolution randomization. It requires order 1/sqrt delta steps to find an optimal solution with bounded error probability, where delta is the minimum spectral gap of the stocha...

so far various methods for optimization presented and one of most popular of them are optimization algorithms based on swarm intelligence and also one of most successful of them is particle swarm optimization (pso). prior some efforts by applying fuzzy logic for improving defects of pso such as trapping in local optimums and early convergence has been done. moreover to overcome the problem of i...

Introduction: To develop different radiomic models based on radiomic features and machine learning methods to predict early intensity modulated radiation therapy (IMRT) response.   Materials and Methods: Thirty prostate patients were included. All patients underwent pre ad post-IMRT T2 weighted and apparent diffusing coefficient (ADC) magnetic resonance imagi...

We present an algorithm for performing rigid-body Brownian dynamics that can take into account the hydrodynamic properties (translational and rotational friction tensors and the coupling between them) of each rigid body. In the zero temperature limit, the error term scales as Delta;{4} for time step Delta , while at nonzero temperatures the error scaling is Delta;{5/2} . We test the algorithm b...

ABSTRACT Difficulties and limitations of the LMS (regression) algorithm are discussed. Although regression algorithms and minimum distance classifiers are very fast, they usually converge to the wrong solution. The proposed modified regression algorithm produces the same results as the delta (back propagation) algorithm, however, it only requires two to three iterations versus the 10,000 iterat...

Sleep and wakefulness are no longer to be considered as discrete states. During wakefulness brain regions can enter a sleep-like state (off-periods) in response to a prolonged period of activity (local use-dependent sleep). Similarly, during nonREM sleep the slow-wave activity, the hallmark of sleep plasticity, increases locally in brain regions previously involved in a learning task. Recent st...

nowadays project management is a key component in introductory operations management. the educators and the researchers in these areas advocate representing a project as a network and applying the solution approaches for network models to them to assist project managers to monitor their completion. in this paper, we evaluated project’s completion time utilizing the q-learning algorithm. so the ...