This paper considers the distributed online bandit optimization problem with nonconvex loss functions over a time-varying digraph. This problem can be viewed as a repeated game between a group of online players and an...
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The paper considers a mathematical model of the technical process of external gettering of silicon rods. The purpose of this process is to remove unwanted impurities from silicon. The model of this process is an initi...
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Semantic mapping is a key component of robots operating in and interacting with objects in structured environments. Traditionally, geometric and knowledge representations within a semantic map have only been loosely i...
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Diabetic Mellitus is the most familiar disease around the globe. Long prevalence of diabetes causes several problems related to health. The most common issue is Diabetic Retinopathy (DR). Diabetic retinopathy is a sit...
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The paper studies a molecular jet that is formed during a gas outflow through a circular tube from a vessel and determines geometric characteristics of the vessel that reduce the jet slope. Developed software is appli...
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Current genotype-to-phenotype models, such as polygenic risk scores, only account for linear relationships between genotype and phenotype and ignore epistatic interactions, limiting the complexity of the diseases that...
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The problem of minimizing the cost of using a heterogeneous complex of resources in regional planning is considered. Volumes and directive intervals characterize the works. An algorithm for constructing an admissible ...
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Coverage path planning (CPP) and path motion stabilization (PMS) play crucial roles in a variety of robotics applications, with a particular focus on their significance in precision agriculture. CPP determines optimal...
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ISBN:
(数字)9798350373974
ISBN:
(纸本)9798350373981
Coverage path planning (CPP) and path motion stabilization (PMS) play crucial roles in a variety of robotics applications, with a particular focus on their significance in precision agriculture. CPP determines optimal paths for covering specified target space, while PMS ensures precise movement along these paths. The paper proposes the advancement of CPP and PMS methodologies through the application of modern metaheuristic algorithms and symbolic regression methods. This study addresses a novel problem where the utilization of these methodologies is pursued to develop a universal stabilization system for moving an object along a trajectory, ensuring complete coverage of target space. Metaheuristic algorithms, such as the Grey Wolf Optimizer used in this study, can effectively solve CPP problems by decomposing the target space into subregions and searching for the optimal trajectory to efficiently explore these subregions. PMS utilizes symbolic regression methods and machine learning control techniques to develop stabilization systems. The control function of the stabilization system is considered as a function of the deviation from the equilibrium state. Consequently, it becomes feasible to explicitly derive a universal stabilization system for subsequent integration into the control object. The proposed CPP and PMS methodologies are evaluated through a computational experiment centered on crop monitoring using a quadcopter, thereby validating their effectiveness in practical applications.
The computational schemes that are supposed to be used in the processes of processing operational information in real-time systems are considered. Two algorithms for scheduling jobs that do not allow interruption and ...
The computational schemes that are supposed to be used in the processes of processing operational information in real-time systems are considered. Two algorithms for scheduling jobs that do not allow interruption and switching are proposed in real-time multiprocessor computing systems. The first algorithm, based on the branch and bound method, solves the speed problem. Processors may differ in their performance. The main feature of this algorithm is that the lower and upper estimates of the length of the optimal schedule are calculated using recurrent relations, which increases its efficiency. The second algorithm solves the problem of finding an admissible schedule in the case when all processors are identical and the directive intervals of all jobs are the same. The algorithm has pseudopolynomial complexity when the number of processors is fixed. A description of the parallel implementation of the algorithm is given.
In this paper, a multi-server resource loss system with resource requirement-dependent service times is considered. We develop a convolutional algorithm for the evaluation of the stationary probability distribution an...
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