Some research results by risk-inform approaches for npp safety and operational efficiency by Yu. А. Komarov

“…In the article the per-spective problems of further development risk-oriented approach (ROA) for the grounding and realization of measures on increase of safety and operational efficiency of NPP are considered. Unlike the traditional approach for the ROA, mean due the definition of probabilistic and/or deterministic methods of risk parameters, as criterion functions essence and the measure of the estimation are defined by the solution of specific problem in nuclear field. …”
Get full text

Efficient Software Development Effort Estimation Approaches for Improving Scalability in the Training Phase by Ho Le Thi Kim Nhung, Petr Silhavy, Radek Silhavy

“…While clustering can address this complexity, standard methods often rely on random initial centers, leading to inconsistent and less precise results. …”
Get full text

Efficient planning and optimization of integrated energy system considering double uncertainty of source and load by LI Aiwu, DI Liang, DONG Jie, TIAN Zhe, WANG Yi, NIU Jide

“…The design process of integrated energy system will face the uncertainty of renewable energy generation and energy demand, and the risk of sub-optimal decision will be introduced when the deterministic method is used for design. In this paper, an efficient planning and optimization model for integrated energy systems considering dual source-load uncertainty was proposed. …”
Get full text

DEVELOPING A CONTROLLER FOR AN ADAPTIVE CRUISE CONTROL (ACC) SYSTEM: UTILIZING DEEP REINFORCEMENT LEARNING (DRL) APPROACH by Ali RIZEHVANDI, Shahram AZADI

Get full text

Optimization Research on Energy Management Strategies and Powertrain Parameters for Plug-In Hybrid Electric Buses by Lufeng Wang, Juanying Zhou, Jianyou Zhao

“…Subsequent to this, a combined multi-layer powertrain optimization method based on Genetic Algorithm-Optimal Adaptive Control of Motor Efficiency-Particle Swarm Optimization (GOP) is proposed. …”
Get full text

Novel efficient deep reinforcement learning-based load frequency control for isolated microgrid by Xin Shen, Yijing Zhang, Jiahao Li, Yitao Zhao, Jianlin Tang, Bin Qian, Xiaoming Lin

“…In addition, a novel sort replay actor critic technique is proposed, leveraging the deep deterministic policy gradient algorithm and sort experience replay to enhance control efficiency and robustness. …”
Get full text

Energy efficient control of indoor environments under time-varying multi-parameter uncertainty by Jianhao ZHAO, Hua SONG, Xinyuan NAN, Xin CAI

Get full text

Efficient Robot Manipulation via Reinforcement Learning with Dynamic Movement Primitives-Based Policy by Shangde Li, Wenjun Huang, Chenyang Miao, Kun Xu, Yidong Chen, Tianfu Sun, Yunduan Cui

“…The proposed method naturally integrates a DMP-based policy into the actor–critic framework of the traditional RL approach Deep Deterministic Policy Gradient (DDPG) and derives the corresponding update formulas to learn the networks that properly decide the parameters of DMPs. …”
Get full text

Deterministic Quantum Dense Coding Based on Non-Maximal Entangled Channel by Xuanxuan Xin, Zhixing Li, Zhen Wang

“…Our scheme represents a substantial improvement over existing probabilistic methods and paves the way for more efficient quantum communication protocols.…”
Get full text

Transforming user story definition: From deterministic to AI-powered automation by Andra-Paula AVASILOAIE, Augustin SEMENESCU, Eduard-Cristian POPOVICI, Ionuț-Cosmin CHIVA

“…Despite its efficiency, the deterministic tool lacked adaptability across different domains. …”
Get full text

Deterministic nanoantenna array design for stable plasmon-enhanced harmonic generation by Jeong Tae-In, Oh Dong Kyo, Kim San, Park Jongkyoon, Kim Yeseul, Mun Jungho, Kim Kyujung, Chew Soo Hoon, Rho Junsuk, Kim Seungchul

“…This spatial beam inhomogeneity can cause power instability of the emitted harmonics when the lateral beam position is not stable which we observed in plasmon-enhanced third-harmonic generation (THG). Hence, we propose a method for deterministically designing the density of a nanoantenna array to decrease the instability of the beam position-dependent THG yield. …”
Get full text

Mode Coresets for Efficient, Interpretable Tensor Decompositions: An Application to Feature Selection in fMRI Analysis by Ben Gabrielson, Hanlu Yang, Trung Vu, Vince Calhoun, Tulay Adali

“…These methods’ efficiencies are often due to their randomized natures; however, deterministic methods can provide better approximations, and can perform feature selection, highlighting a meaningful subset that well-represents the entire tensor. …”
Get full text

Energy-efficient control of thermal comfort in multi-zone residential HVAC via reinforcement learning by Zheng-Kai Ding, Qi-Ming Fu, Jian-Ping Chen, Hong-Jie Wu, You Lu, Fu-Yuan Hu

“…Energy efficient control of thermal comfort has been already an important part of residential heating, ventilation, and air conditioning (HVAC) systems. …”
Get full text

Fast and Deterministic Underwater Point Cloud Registration for Multibeam Echo Sounder Data by Liang Zhao, Lan Cheng, Tingfeng Tan, Chun Cao, Feihu Zhang

“…Given the prevalence of outliers and noise in underwater acoustic measurements, the BnB method is employed to provide globally deterministic solutions. …”
Get full text

OPERATIONAL ANALYSIS OF COMPLEX MEDICAL STATES BY PHOTONICS METHODS by A. I. Larkin, K. A. Trukhanov

“…Such an analysis is carried out by the means of vector-matrix multiplication using laser photonics methods. It is significant that with the widening of the range of probability algorithms, it is possible to preserve certain advantages of the holographic method: multidimensionality, efficiency, high information capacity and speed, visibility and flexibility of the result presentation. …”
Get full text

AI-assisted super-resolution cosmological simulations IV: An emulator for deterministic realizations by Xiaowen Zhang, Patrick Lachance, Ankita Dasgupta, Rupert A. C. Croft, Tiziana Di Matteo, Yueying Ni, Simeon Bird, Yin Li

Get full text

RL-QPSO net: deep reinforcement learning-enhanced QPSO for efficient mobile robot path planning by Yang Jing, Li Weiya

“…These methods have high computational costs and are not efficient for real-time applications.MethodsTo address these issues, this paper presents a Quantum-behaved Particle Swarm Optimization model enhanced by deep reinforcement learning (RL-QPSO Net) aimed at improving global optimality and adaptability in path planning. …”
Get full text

A DRL-based optimization method for microgrid operation by ZENG Lei, DING Quan, CHEN Xiaoyu, YUE Xianya

“…Third， a penalty term for high-proportion erroneous actions is incorporated into the reward function to constrain the output of each device within a reasonable range， mitigating the risk of insufficient safety guarantees inherent in reinforcement learning methods. Finally， simulation results demonstrate that， compared to the deep deterministic policy gradient （DDPG） algorithm， the proposed method achieves superior economic efficiency and stability， with economic costs closer to those of ideal deterministic optimization methods.…”
Get full text

Hybrid lion and exponential PSO-based metaheuristic clustering approach for efficient dynamic data stream management by M. Ananthi, K. Valarmathi, A. Ramathilagam, R. Praveen

“…It adopted different methods of stochastic optimization and deterministic clustering techniques for centring the clusters in an optimal manner. …”
Get full text

Spectral clustering-based energy-efficient resource allocation algorithm in heterogeneous cellular ultra-dense network by Xue WANG, Jing LIU, Jiani SUN, Jizhen ZHANG, Zhihong QIAN

“…In order to solve problems of high power consumption, spectrum shortage and low energy efficiency in the ultra-intensive 5G mobile communication scenario, a resource allocation algorithm based on the maximum energy efficiency for the two-layer heterogeneous cellular non-orthogonal multiple access network was proposed.The original NP-hard optimization problem on the downlink communication link of ultra-dense scene was divided into two subproblem, such as frequency resource allocation and power allocation, which became a deterministic constraint optimization problem.The frequency resource allocation scheme of different user groups was obtained by using base station clustering based on the improved k-means algorithm and users grouping based on spectral clustering algorithm.The fraction of energy efficiency optimization was transformed into a solvable continuous convex optimization problem and power distribution was realized by Dinkelbach method, and the Lagrange multiplier iterative algorithm, respectively.Jointly optimize system energy efficiency in terms of base station clustering, user grouping, resource block allocation and power allocation, which minimized the inter-cluster interference and intra-cluster interference of the base station efficiently.The simulation results show that the proposed algorithm is better on energy efficiency and computational efficiency compared with existing algorithms.…”
Get full text