FUZZY ALGORITHM TO CONTROL REACTIVE POWER FLOW IN ELECTRIC NETWORK WITH NONLINEAR LOADS by H. B. Guliyev

“…The commonly used methods for compensation of harmonic currents by filtering devices make it possible to solve the problem in a narrow band of variation of current of a nonlinear load. In the reality stochastic character of power consumption of nonlinear load reveals itself in appropriate changes in harmonic components of voltage and their share in total load current. …”
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Reliability Prediction of Ontology-Based Service Compositions Using Petri Net and Time Series Models by Jia Li, Yunni Xia, Xin Luo

“…In this study, we consider the runtime quality of services to be fluctuating and introduce a dynamic framework to predict the runtime reliability of services specified in OWL-S, employing the Non-Markovian stochastic Petri net (NMSPN) and the time series model. …”
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Fault aware task scheduling in cloud using min-min and DBSCAN by S.M.F D Syed Mustapha, Punit Gupta

“…Density-based spatial clustering of applications with noise (DBSCAN) is a stochastic approach-based algorithm which has the capability to cluster the resources in a cloud environment. …”
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Efficient Computation of Multiscale Entropy over Short Biomedical Time Series Based on Linear State-Space Models by Luca Faes, Alberto Porta, Michal Javorka, Giandomenico Nollo

“…To overcome these limitations, we propose a method to assess RMSE for autoregressive (AR) stochastic processes. The method makes use of linear state-space (SS) models to provide the multiscale parametric representation of an AR process observed at different time scales and exploits the SS parameters to quantify analytically the complexity of the process. …”
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An Integrative Approach to Understand the Climatic-Hydrological Process: A Case Study of Yarkand River, Northwest China by Jianhua Xu, Yiwen Xu, Chunan Song

“…The main findings are as follows. (1) The hydrologic and climatic variables, that is, annual runoff (AR), annual average temperature, (AAT) and annual precipitation (AP), are stochastic and, no significant autocorrelation. (2) The variation patterns of runoff, temperature, and precipitation were scale dependent in time. …”
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Probabilistic Forecasting of Crude Oil Prices Using Conditional Generative Adversarial Network Model with Lévy Process by Mohammed Alruqimi, Luca Di Persio

“…This paper introduces a Crude Oil-Driven Conditional GAN (CO-CGAN), a hybrid model for enhancing crude oil price forecasting by combining advanced AI frameworks (GANs), oil market sentiment analysis, and stochastic jump-diffusion models. By employing conditional supervised training, the inherent structure of the data distribution is preserved, thereby enabling more accurate and reliable probabilistic price forecasts. …”
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Dynamic Prediction for Accuracy Maintaining Reliability of Superprecision Rolling Bearing in Service by Liang Ye, Xintao Xia, Zhen Chang

“…A dynamic prediction method for accuracy maintaining reliability (AMR) of superprecision rolling bearings (SPRBs) in service is proposed by effectively fusing chaos theory and grey system theory and applying stochastic processes. In this paper, the time series of a vibration signal is used to characterize the state information for SPRB, and four runtime data points can be predicted in the future, which depends on four chaotic forecasting models to preprocess the time series. …”
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High-resolution fleezers reveal duplex opening and stepwise assembly by an oligomer of the DEAD-box helicase Ded1p by Eric M. Patrick, Rajeev Yadav, Kasun Senanayake, Kyle Cotter, Andrea A. Putnam, Eckhard Jankowsky, Matthew J. Comstock

“…Using high-resolution optical tweezers and fluorescence, we reveal a highly dynamic and stochastic process of multiple Ded1p protomers assembling on and unwinding an RNA duplex. …”
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Enhanced Bearing Fault Detection Using Step-Varying Vibrational Resonance Based on Duffing Oscillator Nonlinear System by Yongbin Liu, Zhijia Dai, Siliang Lu, Fang Liu, Jiwen Zhao, Jiale Shen

“…Experimental results show that SVVR is more effective in extracting weak characteristic information than other methods, including multiscale noise tuning stochastic resonance (SR), Woods–Saxon potential-based SR, and joint Woods–Saxon and Gaussian potential-based SR. …”
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The Kramers escape rate of phase transitions for the 6-dimensional Gauss-Bonnet AdS black hole with triple phases by Chen Ma, Pan-Pan Zhang, Bin Wu, Zhen-Ming Xu

“…In this study, we obtain specific picture of the phase transitions for the 6-dimensional Gauss-Bonnet Anti-de Sitter (AdS) black hole with triple phases, using the generalized free energy we constructed and Kramers escape rate in stochastic motion. There are six possible phase transition processes between the three different stable states (small, medium, and large black hole states). …”
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ECONOMIC ANALYSIS OF SOIL-BASED AND SOILLESS FARMING SYSTEMS: A CASE STUDY FROM DA LAT CITY by Đặng Đức Huy, Phạm Thị Thuyền, Đàm Thị Hải Âu, Trần Thanh Giang, Nguyễn Thị Trà My

“…The sensitivity analysis of soil-based systems reveals that the impact of stochastic inputs is in the decreasing magnitude of interest, gross revenue, and total operating cost. …”
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Hybridized Extreme Learning Machine Model with Salp Swarm Algorithm: A Novel Predictive Model for Hydrological Application by Zaher Mundher Yaseen, Hossam Faris, Nadhir Al-Ansari

“…The capability of the extreme learning machine (ELM) model in modeling stochastic, nonlinear, and complex hydrological engineering problems has been proven remarkably. …”
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Efficiency Analysis of Turkish Container Ports: SFA or DEA? by İsmail Yenilmez

“…Purpose: The study compares the efficiency of Turkish container ports using Stochastic Frontier Analysis and Data Envelopment Analysis. …”
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Using an SGB Decision Tree Approach to Estimate the Properties of CRM Made by Biomass Pretreated with Ionic Liquids by Ya-Qing Gu, Tao Shu, Bin Ge, Ping Wang, Chen Gao, Hamid Heydari

“…In this research, due to the wide range of applications and ease of using artificial intelligence procedures, on the basis of the algorithm of stochastic gradient boosting (SGB) decision tree, an artificial intelligence approach is proposed to estimate the properties of cellulose-rich materials (CRMs). …”
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Optimal Preference Satisfaction for Conflict-Free Joint Decisions by Hiroaki Shinkawa, Nicolas Chauvet, Guillaume Bachelier, André Röhm, Ryoichi Horisaki, Makoto Naruse

“…However, probabilistic preferences appear naturally in relation to the stochastic decision-making of humans, and therefore, we theoretically derive conflict-free joint decision-making that satisfies the probabilistic preferences of all individual players. …”
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A Software Tool for Assisting Experimentation in Dynamic Environments by Pavel Novoa-Hernández, Carlos Cruz Corona, David A. Pelta

“…In this context, experimentation is a crucial task because of the stochastic nature of both algorithms and problems. Currently, there are several technologies whose methods, problems, and performance measures can be implemented. …”
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Resilient Schedule Coordination for a Bus Transit Corridor by Xiongfei Lai, Jing Teng, Paul Schonfeld, Lu Ling

“…Timed transfers that schedule vehicles from various routes to arrive at some transfer stations simultaneously (or nearly so) can significantly reduce wait times in transit networks, while stochastic passenger flows and complex operating environments may reduce this improvement. …”
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Stock status of kawakawa Euthynnus affinis (Cantor, 1849) fishery using surplus production model: An assessment from coastal waters of Tamil Nadu, Bay of Bengal, Southeast coast of... by Rajendran Abinaya, Moosambikandy K. Sajeevan

“…The Catch-based MSY (CMSY), the Bayesian state-space Schaefer surplus production Model (BSM), and stochastic Surplus Production model in Continuous Time (SPiCT) packages were used to investigate the stock exploitation by running surplus production models with catch, catch per unit effort (CPUE), and other life history data. …”
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Analysis of Constraint-Handling in Metaheuristic Approaches for the Generation and Transmission Expansion Planning Problem with Renewable Energy by Lourdes Martínez-Villaseñor, Hiram Ponce, José Antonio Marmolejo-Saucedo, Juan Manuel Ramírez, Agustina Hernández

“…This model integrates conventional generation with renewable energy sources, assuming a stochastic approach. The proposed approach is based on a centralized planned transmission expansion. …”
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Bio-Inspired Jumping Spider Optimization for Controller Tuning/Parameter Estimation of an Uncertain Aerodynamic MIMO System by Ravi Samikannu, Oduetse Matsebe, David Ezekiel

“…Counter to other algorithms (deterministic and stochastic) that get caught in local minima, JSOA evolved a solution after searchingly rummaging the entire solution search space in a vectorized fashion for an optimal value. …”
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