An integrated control framework for the yaw and roll stability of autonomous vehicles based on interval type-2 fuzzy logic (IT2 FL) is presented in this research. Firstly, to describe the lateral, yaw and roll motion ...
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A pricing mechanism for the charging schedule problem of Electric Vehicles (EVs) that takes into account the requests of EVs is proposed. Conventional price schemes adopted in the literature are typically affected by ...
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The proceedings contain 29 papers. The special focus in this conference is on Mathematical Optimization Theory and Operations Research. The topics include: On the Resource Allocation Problem to Increase Reli...
ISBN:
(纸本)9783031353048
The proceedings contain 29 papers. The special focus in this conference is on Mathematical Optimization Theory and Operations Research. The topics include: On the Resource Allocation Problem to Increase Reliability of Transport Systems;distributionally Robust Optimization by Probability Criterion for Estimating a Bounded Signal;approximation Algorithms for Two-Machine Proportionate Routing Open Shop on a Tree;MIP Heuristics for a Resource Constrained Project Scheduling Problem with Workload Stability Constraints;hybrid Evolutionary Algorithm with Optimized Operators for Total Weighted Tardiness Problem;equilibrium Arrivals to Preemptive Queueing System with Fixed Reward for Completing Request;on Optimal Positional Strategies in Fractional Optimal Control Problems;on a Single-Type Differential Game of Retention in a Ring;harmonic Numbers in Gambler’s Ruin Problem;on Decentralized Nonsmooth Optimization;exploitation and Recovery Periods in Dynamic Resource Management Problem;trade-Off Mechanism to Sustain Cooperation in Pollution Reduction;communication Restriction-Based Characteristic Function in Differential Games on Networks;guaranteed Expectation of the Flock Position with Random Distribution of Items;method for Solving a Differential Inclusion with a Subdifferentiable Support Function of the Right-Hand Side;approximate Solution of Small-Time Control Synthesis Problem Based on Linearization;a Priori Estimates of the Objective Function in the Speed-in-Action Problem for a Linear Two-Dimensional Discrete-Time System;an Approach to Solving Input Reconstruction Problems in Stochastic Differential Equations: Dynamic Algorithms and Tuning Their Parameters;mathematical Modeling of the Household Behavior in the Labor Market;visual Positioning of a Moving Object Using Multi-objective Control Algorithm;byzantine-Robust Loopless Stochastic Variance-Reduced Gradient;Semi-supervised K-Means Clustering via DC programming Approach;on the Uniqueness of Identification the Thermal
Automated monitoring of tool wear is crucial for maintaining product quality. Furthermore, implementing AI techniques for real-time tool monitoring involves not only developing models but also managing their versions,...
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Along with the development of the times, bitcoin and gold obtained more and more people's hot pursuit. However, the frequent price changes, especially for the rapid price changes of bitcoin, cause great suffering ...
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Neuro-symbolic integration aims at harnessing the power of symbolic knowledge representation combined with the learning capabilities of deep neural networks. In particular, logic Tensor Networks (LTNs) allowto incorpo...
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ISBN:
(纸本)9783031431524;9783031431531
Neuro-symbolic integration aims at harnessing the power of symbolic knowledge representation combined with the learning capabilities of deep neural networks. In particular, logic Tensor Networks (LTNs) allowto incorporate background knowledge in the form of logical axioms by grounding a first order logic language as differentiable operations between real tensors. Yet, few studies have investigated the potential benefits of this approach to improve zero-shot learning (ZSL) classification. In this study, we present the Fuzzy logic Visual Network (FLVN) that formulates the task of learning a visual-semantic embedding space within a neuro-symbolic LTN framework. FLVN incorporates prior knowledge in the form of class hierarchies (classes and macro-classes) alongwith robust high-level inductive biases. The latter allow, for instance, to handle exceptions in class-level attributes, and to enforce similarity between images of the same class, preventing premature overfitting to seen classes and improving overall performance. FLVNreaches state of the art performance on the Generalized ZSL (GZSL) benchmarksAWA2andCUB, improving by 1.3% and 3%, respectively. Overall, it achieves competitive performance to recent ZSL methods with less computational overhead. FLVN is available at https://***/grains2/flvn.
Many important properties of multi-agent systems refer to the participants' ability to achieve a given goal, or to prevent the system from an undesirable event. Among intelligent agents, the goals are often of epi...
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