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901
Algorithm for Dynamic Reactive Power Optimization of Regional Power Grid Based on Interior Point Method and Neighborhood Search Decoupling Dynamic Programming Method
Published 2023-02-01“…The two-stage method could not only ensure the quality of the optimal solution, but also avoid solving the state combination explosion problem with discrete variables, which greatly improves the computational efficiency. …”
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902
Safety Assessment of Loop Closing in Active Distribution Networks Based on Probabilistic Power Flow
Published 2025-05-01“…By modeling DGs and loads as random variables, their cumulants are efficiently obtained through LHS. …”
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903
Principal networks.
Published 2013-01-01“…Graph-theoretic measures of network cost and efficiency may be calculated separately for each principal network. …”
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904
Removal of caffeine from aqueous solution by green approach using Ficus Benjamina zero-valent iron/copper nanoparticles
Published 2020-12-01“…Overall, FB-Fe/Cu is a committed green substance for removal Caffeine from aqueous solutions. Functional parameters affect investigated using the Linear regression analysis, we found them to account for over 98% of the variables affecting the removal procedure.…”
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905
Beyond Collaboration: The Impact of Partner Knowledge, Relational Skills, and Internal Communication on SME’s Performance
Published 2025-04-01“…This finding confirms that effective network capability management can improve competitiveness, operational efficiency, and innovation in SME Performance. …”
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906
Soil moisture and precipitation intensity jointly control the transit time distribution of quick flow in a flashy headwater catchment
Published 2025-08-01“…The results showed that accounting for both soil moisture and precipitation intensity to define the shape of SAS functions for preferential flow improved the tracer simulation in streamflow (increasing the Nash–Sutcliffe efficiency from 0.31 to 0.51). …”
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907
Explainable AI-driven assessment of hydro climatic interactions shaping river discharge dynamics in a monsoonal basin
Published 2025-07-01“…The main findings of this study are (1) KAN demonstrated high predictive performance with root mean squared error (RMSE) values ranging from 42.7 to 58.3 m3/s, Nash–Sutcliffe efficiency (NSE) between 0.80 and 0.87, mean absolute error (MAE) between 28.9 to 52.7 and R2 values between 0.84 and 0.90 across stations. (2) SHAP based feature contribution analysis identified Relative humidity (hurs), specific humidity (huss), and temperature (tas) as key predictors, while (pr) showed limited contribution due to spatial inherent inconsistencies in GCM precipitation data. (3) The bootstrapped SHAP distributions highlighted substantial variability in feature importance, particularly for humidity variables, revealing station specific uncertainty patterns in model interpretation. (4) The KAN framework results indicate strong temporal alignment and physical realism, confirming KAN’s robustness in capturing seasonal discharge dynamics and extreme flow events under monsoon influence environments. (5) In this study KAN with SHAP (SHapley additive exPlanations) is implemented for hydrological modeling under monsoon-influenced and data-limited regions such as SRB, offering improved accuracy, functional precision and efficiency compared to traditional models. …”
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908
Optimized integration of photovoltaic systems and distribution static compensators in distribution networks using a novel discrete-continuous version of the adaptive JAYA algorithm...
Published 2025-06-01“…For comparison, the discrete-continuous versions of the vortex search algorithm (VSA), the sine-cosine algorithm (SCA), Phasor Particle Swarm Optimization (PPSO), New Self-Organising Hierarchical PSO (NHPSO-JTVAC), Differential Evolution (DE), Gold Search Optimization (GSO) and the classical version of JAYA are used, validating the effectiveness of our proposal on the 33- and 69-bus test systems while considering variable generation and demand. In terms of the best solution, the average solution, and the required processing times, the AJAYA-SA strategy yields the best results in both test systems, making it the most efficient method to solve the problem under study.…”
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909
Shell and tube heat exchanger optimization: A critical literature assessment and fairness-based comparative performance analysis of meta-heuristic algorithms
Published 2025-08-01“…In order to make comparisons, the objective function, decision variables and their boundary values were taken as the same. …”
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910
Computational studies reveal structural characterization and novel families of Puccinia striiformis f. sp. tritici effectors.
Published 2025-03-01“…However, due to the lack of an efficient genetic transformation system in Pst, progress in effector function studies has been slow. …”
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911
Comparing the Effect of Beractant (Beraksurf™) with That of Poractant Alfa (Curosurf®) on the Need for Intermittent Positive Pressure Ventilation in Neonatal Respiratory Distress S...
Published 2025-02-01“…Performing appropriate adjusted analysis leads to a more interpretable and efficient estimation of treatment effects. Semiparametric adjustment approach modifies the estimating equations solved by the marginal treatment effect estimator by adding an augmentation function, which makes use of the baseline covariates and estimate the unbiased marginal treatment effect with improved precision. …”
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912
Multi-objective optimal scheduling of cascade reservoirs in complex basin systems: Case study of the Jinsha River-Yalong River confluence basin in China
Published 2025-04-01“…In complex basins with multiple converging rivers, the ''dimensional catastrophe'' effect increases with more decision variables, requiring improved robustness and optimization of the scheduling algorithm. …”
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913
Shunt active power filter using model predictive control with stability guarantee
Published 2025-06-01“…This paper presents a model predictive control (MPC) strategy to solve an optimization problem based on system state and control variables, subject to constraints imposed by the control objective. …”
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914
Sustainable PV-hydrogen-storage microgrid energy management using a hierarchical economic model predictive control framework
Published 2025-02-01“…First, a precise nonlinear model of the PHS microgrid is established and the logic variables are introduced to capture the hydrogen devices’ short-term properties, i.e., the start-up/shut-down of electrolyzers and fuel cells. …”
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915
A 3D mixed frame element with multi-axial coupling for thin-walled structures with damage
Published 2014-07-01“…An efficient algorithm is formulated for the element state determination, based on a consistent linearization of the governing equations. …”
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916
Decarbonisation pathways for industrial clusters through multi-energy systems
Published 2025-06-01“…Given the complex and nonlinear interconnections among systems within a multi-energy cluster, this study extends the dynamic multi-vector methodology to multi-energy system clusters, representing variables as nodes and converting them into transfer functions for system integration. …”
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917
Experiments in globalisation, food security and land use decision making.
Published 2014-01-01“…Both outcomes are subject to the responses of individual land managers to economic and environmental stimuli, and these responses are known to be variable and often (economically) irrational. We investigate the consequences of stylised food security policies and globalisation of agricultural markets on land use patterns under a variety of modelled forms of land manager behaviour, including variation in production levels, tenacity, land use intensity and multi-functionality. …”
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918
Developing a machine learning model for fast economic optimization of solar power plants using the hybrid method of firefly and genetic algorithms, case study: optimizing solar the...
Published 2024-12-01“…The objective functions were to optimize the exergy efficiency and the heat cost. …”
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919
Building electrical consumption patterns forecasting based on a novel hybrid deep learning model
Published 2025-06-01“…Specifically, the proposed model comprises three key components: (i) a mutual information-based feature selection method to identify the most significant input variables influencing energy consumption; (ii) a variational mode decomposition (VMD) approach to decompose the original energy consumption signal into intrinsic mode functions (IMFs), capturing relevant trends and eliminating noise; and (iii) a long short-term memory (LSTM) neural network to perform time-series forecasting of the target energy consumption values. …”
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920
The Relationship between the Reorganization of Higher Education Institutions' Operations in Poland During the COVID-19 Pandemic and Student Loyalty
Published 2024-12-01“…Using exploratory factor analysis (EFA), the main components were identified for various variables pertaining to the functioning, organization, and delivery of online classes, as well as for aspects associated with university operations during the COVID-19 pandemic. …”
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