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Efficient Deterministic Anchor Deployment for Sensor Network Positioning
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AN EFFICIENT SPEECH GENERATIVE MODEL BASED ON DETERMINISTIC/STOCHASTIC SEPARATION OF SPECTRAL ENVELOPES
Published 2020-03-01“…The paper presents a speech generative model that provides an efficient way of generating speech waveform from its amplitude spectral envelopes. …”
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Deep deterministic policy gradient-based energy efficiency optimization algorithm for CR-NOMA
Published 2024-05-01“…By jointly optimizing the transmission power and time slot splitting coefficient, the energy efficiency of sensor devices was improved. The energy efficiency optimization problem was modeled as a Markov decision process, and it was solved by the deep deterministic policy gradient (DDPG) method. …”
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Optimizing HVAC&R System Efficiency and Comfort Levels Using Machine Learning-Based Control Methods
Published 2025-05-01Get full text
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Hybrid Deterministic Sensing Matrix for Compressed Drone SAR Imaging and Efficient Reconstruction of Subsurface Targets
Published 2025-02-01“…The limited processing capacity and memory resources of small SAR platforms demand efficient recovery performance for high-resolution imaging. …”
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Recursive Objective Space Exploration (ROSE): A computationally efficient deterministic approach for bi-objective optimization.
Published 2025-01-01“…These include a more computationally efficient method for solving bi-objective optimization problems, an adaptive representation of the Pareto front based on trade-offs, and intuitive, straightforward parameterization guided by a user-oriented, trade-offs based stopping criterion.…”
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UAVs's efficient controlled mobility management for mobile heterogeneous wireless sensor networks
Published 2022-06-01“…According to experiments, the proposed deterministic and genetic methods can efficiently deal with the complexity of Mobile Heterogeneous WSNs compared to the previously applied random strategies. …”
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Enhancing cold storage efficiency: Continuous deep deterministic policy gradient approach to energy optimization utilizing strategic sensor input data
Published 2025-04-01“…In this study, we present a continuous Deep Deterministic Policy Gradient (DDPG)-based control algorithm applied to extended-scale cold storage environments to optimize energy efficiency. …”
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Reinforcement Learning-Driven Secrecy Energy Efficiency Maximization in RIS-Enabled Communication Systems
Published 2025-01-01“…Our extensive simulations show that our method works much better than current techniques using deterministic policy gradients, like the proximal policy optimization (PPO) framework, in improving SEE. …”
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Hybrid Fuzzy–DDPG Approach for Efficient MPPT in Partially Shaded Photovoltaic Panels
Published 2025-04-01“…The proposed algorithm is evaluated in a simulated PV environment under various shading scenarios and benchmarked against conventional Perturb and Observe P&O and IC methods. Experimental results demonstrate that the Fuzzy–DDPG approach outperforms these classical techniques by achieving a higher tracking efficiency of 95%, compared to 85% for P&O and 88% for IC in average, while also minimizing steady-state oscillations. …”
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Implementing Low Latency and High Energy Efficiency Task Scheduling in MEC Systems Using Improved DDPG Algorithm
Published 2024-01-01“…This paper presented a method that improves the Deep Deterministic Policy Gradient (DDPG) algorithm for better performance in MEC systems. …”
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An Efficient Polynomial Chaos Method for Stiffness Analysis of Air Spring Considering Uncertainties
Published 2021-01-01“…Traditional methods for stiffness analysis of the air spring are based on deterministic assumption that the parameters are fixed. …”
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BIT*+TD3 Hybrid Algorithm for Energy-Efficient Path Planning of Unmanned Surface Vehicles in Complex Inland Waterways
Published 2025-03-01“…By bridging sampling-based planning methods with deep reinforcement learning methods, this research advances autonomous navigation technology and provides a scalable and energy-efficient solution for maritime applications.…”
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Direct 3D Method of Characteristic Based on Efficient Characteristic Tracing and On-the-fly Generation
Published 2025-01-01“…The method of characteristics (MOC) is one of the excellent implementations of the next generation of neutronic deterministic calculations due to its powerful geometric processing capabilities and natural parallelism. …”
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More bang for your buck: potential gains through optimizing maize breeding schemes in sub-Saharan Africa
Published 2025-06-01“…Our results highlight how a simple deterministic model can identify steps to greatly improve breeding efficiency within resource-constrained breeding programs.…”
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Deterministic Calculation Method for Continuous-energy Neutron Transport Equation in No-resonance Energy-range
Published 2024-06-01“…Although the probabilistic method could be calculated based on the continuous energy library, the computational efficiency could not meet the needs of large-scale engineering calculations. …”
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Efficient TD3 based path planning of mobile robot in dynamic environments using prioritized experience replay and LSTM
Published 2025-05-01“…Abstract To address the challenges of sample utilization efficiency and managing temporal dependencies, this paper proposes an efficient path planning method for mobile robot in dynamic environments based on an improved twin delayed deep deterministic policy gradient (TD3) algorithm. …”
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Efficient Finite-Difference Estimation of Second-Order Parametric Sensitivities for Stochastic Discrete Biochemical Systems
Published 2024-12-01“…This strategy utilizes adaptive tau-leaping schemes and coupling of the perturbed and nominal processes for an efficient sensitivity estimation. The advantages of the new technique are demonstrated through its application to several biochemical system models with practical significance.…”
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A Practical Bearing Failure Detection Method Using a New Efficient Deep Network With the Knowledge Self-Adaptive Evolution
Published 2025-01-01“…To address this issue, a practical bearing failure detection method using a new efficient deep network with the knowledge self-adaptive evolution, named autonomous compression method based on network pruning and knowledge distillation (AMC-NPKD), is proposed in this paper. …”
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