Benchmarking reinforcement learning and accurate modeling of ground source heat pump systems: Intelligent strategy using spiking recurrent neural network combined with spider WASP... by Sana Qaiyum, Kashif Irshad, Mohamed E. Zayed, Salem Algarni, Talal Alqahtani, Asif Irshad Khan

“…Ground source heat pump (GSHP) has recently gained a great attention because of its efficient utilization of geothermal energy for building cooling and heating. …”
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Mapping topographic structure in white matter pathways with level set trees. by Brian P Kent, Alessandro Rinaldo, Fang-Cheng Yeh, Timothy Verstynen

“…Using diffusion spectrum imaging data collected on neurologically healthy controls (N = 30), we mapped white matter pathways from the cortex into the striatum using a deterministic tractography algorithm that estimates fiber bundles as dimensionless streamlines. …”
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Effect of Data Assimilation on Basin Evapotranspiration Simulation by YIN Jian, QIU Yuanhong, ZHANG Bin

“…The results show that: The simulation accuracy of TVGM is improved in both Nash-Sutcliffe efficiency coefficient and water balance coefficient through data assimilation. …”
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Interval Uncertainty Analysis for Wheel–Rail Contact Load Identification Based on First-Order Polynomial Chaos Expansion by Shengwen Yin, Haotian Xiao, Lei Cao

“…Traditional methods for identifying wheel–rail contact loads are based on deterministic models, in which the uncertainties such as material inhomogeneity and geometric tolerance are not considered. …”
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Optimization of Flight Scheduling in Urban Air Mobility Considering Spatiotemporal Uncertainties by Lingzhong Meng, Minggong Wu, Xiangxi Wen, Zhichong Zhou, Qingguo Tian

“…Traditional flight plan adjustment and management methods often rely on deterministic trajectory predictions, ignoring the inherent temporal uncertainties in actual operations, which may lead to the underestimation of potential risks. …”
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SENSITIVITY OF THE TECHNICAL CONDITION OF ELECTRICAL EQUIPMENT OF MOBILE ROBOTIC COMPLEXES FOR SOLVING MONITORING TASKS by A.V. Zayara, M.E. Danilin

“…To solve the problem of sensing the technical condition of the electrical equipment of mobile robotic complexes through the integration of sensory information, a monitoring procedure is proposed as an integral part of a maintenance and repair system based on a proactive concept. Materials and methods. Using the method of associative analogy, a comparison of the time-deterministic process of reducing the performance of the robotics complex with a deterioration in human performance has been carried out, which makes it possible to assess the technical condition according to a generalized parameter characterizing the energy efficiency of the RTK using fuzzy logical inference. …”

Analyzing measles spread through a Markovian SEIR model by Yousef Alnafisah, M. A. Sohaly

“…We employ the state reduction method to simplify complex computations and develop a Mathematica-based algorithm to efficiently determine steady-state probabilities. …”
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Modelling of River-Groundwater Interactions under Rainfall Events Based on a Modified Tank Model by Wen Nie, Yong-chang Liang, Lin Chen, Wei Shao

“…The results of the deterministic method of the numerical case and optimized method of the modified tank model matched well.…”
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Using Hybrid Wavelet-Exponential Smoothing Approach for Streamflow Modeling by Vahid Nourani, Hessam Najafi, Alireza Babaeian Amini, Hitoshi Tanaka

“…The obtained results indicated that combining WT with the ES method and ANN led to more accurate modeling. The proposed methodology (WES2) that used all decomposed subseries separately improved the efficiency of models up to 30% and 10% for the daily dataset and up to 88% and 57% for the monthly dataset, respectively, for the West Nishnabotna and Trinity Rivers.…”
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Research on High-Precision Motion Planning of Large Multi-Arm Rock Drilling Robot Based on Multi-Strategy Sampling Rapidly Exploring Random Tree* by Qiaoyu Xu, Yansong Lin

“…This mechanism flexibly applies three sampling methods at different stages of path planning, significantly improving the adaptability and search efficiency of the RRT* algorithm. …”
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The impact of HCV therapy in a high HIV-HCV prevalence population: A modeling study on people who inject drugs in Ho Chi Minh City, Vietnam. by Ruthie B Birger, Thuy Le, Roger D Kouyos, Bryan T Grenfell, Timothy B Hallett

“…Mathematical models have been used to great effect to shape HIV care, but few have been proposed for HIV/HCV.<h4>Methods</h4>We constructed a deterministic compartmental ODE model that incorporated layers for HIV disease progression, HCV disease progression and PWID demography. …”
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Pareto Optimal Solutions for Stochastic Dynamic Programming Problems via Monte Carlo Simulation by R. T. N. Cardoso, R. H. C. Takahashi, F. R. B. Cruz

“…This new idea is carried out by using Monte Carlo simulations embedded in an approximate algorithm proposed to deterministic dynamic programming problems. The new method is tested in instances of the classical inventory control problem. …”
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Multiobjective Transmission Network Planning considering the Uncertainty and Correlation of Wind Power by Yuan Hu, Zhaohong Bie, Yanling Lin, Guangtao Ning, Mingfan Chen, Yujie Gao

“…In order to consider the uncertainty and correlation of wind power in multiobjective transmission network expansion planning (TNEP), this paper presents an extended point-estimation method to calculate the probabilistic power flow, based on which the correlative power outputs of wind farm are sampled and the uncertain multiobjective transmission network planning model is transformed into a solvable deterministic model. …”
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Stochastic simulation of soil moisture dynamics in farmland in the eastern region of the Songnen Plain. by Bo Meng, Jin Wang, Fanxiang Meng, Ennan Zheng, Tianxiao Li, Bowen Tang

“…Soil moisture is the core of the hydrological cycle in agroecosystems, and most of the studies on soil moisture dynamics modeling adopt deterministic research methods, which are not well suited to study the hydrological processes in agricultural fields under changing conditions. …”
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Quantum reinforcement learning in continuous action space by Shaojun Wu, Shan Jin, Dingding Wen, Donghong Han, Xiaoting Wang

“…To overcome this limitation, we introduce a quantum Deep Deterministic Policy Gradient (DDPG) algorithm that efficiently addresses both classical and quantum sequential decision problems in continuous action spaces. …”
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Wide-Range Variable Cycle Engine Control Based on Deep Reinforcement Learning by Yaoyao Ding, Fengming Wang, Yuanwei Mu, Hongfei Sun

“…To solve this problem, this paper adopts a deep reinforcement learning method based on a deep deterministic policy gradient algorithm, and it applies an action space pruning technique to optimize the controller, which significantly improves the convergence speed of network training. …”
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Optimizing Transport Logistics under Uncertainty with Simheuristics: Concepts, Review and Trends by Juliana Castaneda, Elnaz Ghorbani, Majsa Ammouriova, Javier Panadero, Angel A. Juan

“…Generally, the analysis of complex systems in these non-deterministic environments is approached with simulation techniques. …”
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Preventive-Corrective Control for Static Voltage Stability Under Multiple <tex>$N-1$</tex> Contingencies Considering Wind Power Uncertainty by Yuerong Yang, Shunjiang Lin, Qiong Wang, Mingbo Liu, Qifeng Li

“…Case studies on the IEEE-39 bus system and an actual provincial power grid demonstrate the effectiveness and efficiency of the proposed method.…”
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Cost-effectiveness of Triple Therapy with Telaprevir for Chronic Hepatitis C Virus Patients in Germany by Jona T. Stahmeyer, Svenja Schauer, Siegbert Rossol, Hans Heinrich Wedemeyer, Daniel Wirth, Florence Bianic, Christian Krauth

“…Model structure and inputs were discussed with clinical experts. Deterministic and probabilistic sensitivity analyses were performed to verify the robustness of results…”
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Building Energy Optimization Using an Improved Exponential Distribution Optimizer Based on Golden Sine Strategy Minimizing Energy Consumption Under Uncertainty by Mohammad Ali Karbasforoushha, Mohammad Khajehzadeh, Suraparb Keawsawasvong, Lapyote Prasittisopin, Thira Jearsiripongkul

“…The conventional Exponential distribution optimizer (EDO) is improved using the Golden sine strategy to boost search process efficiency and reduce the probability of getting trapped in local optima. …”
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