Suchergebnisse - Bayesian optimization algorithm*
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High-Precision Indoor Visible Light Positioning Using Deep Neural Network Based on the Bayesian Regularization With Sparse Training Point
Veröffentlicht 2019-01-01“… All of the aforementioned experimental results show that the algorithm and training data optimization we proposed provide a new solution for real-time and high-accuracy positioning with the neural network. …”In this letter, we propose an indoor visible light positioning technique that combines deep neural network based on the Bayesian Regularization (BR-DNN) with sparse diagonal training data set. Unlike other neural networks, which require a large number of training data points to locate accurately, we...
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Hyperparameter-tuned variational Bayesian Gaussian mixture model-based fault time detection method for distribution networks with distributed generation
Veröffentlicht 2025-10-01“… The fault self-synchronization method enables cost-effective data synchronization for differential protection in distribution networks but suffers from synchronization errors under complex faults due to detection algorithm sensitivity. To address this, the paper analyzes the delay mechanism in active distribution network fault detection and factors affecting synchronization errors. …”The fault self-synchronization method enables cost-effective data synchronization for differential protection in distribution networks but suffers from synchronization errors under complex faults due to detection algorithm sensitivity. To address this, the paper analyzes the delay mechanism in activ...
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Deconvolution of continuous paleomagnetic data from pass‐through magnetometer: A new algorithm to restore geomagnetic and environmental information based on realistic optimization...
Veröffentlicht 2014-10-01“… The new algorithm was tested using synthetic data constructed by convolving “true” paleomagnetic signal containing an “excursion” with the sensor response. …”Abstract The development of pass‐through superconducting rock magnetometers (SRM) has greatly promoted collection of paleomagnetic data from continuous long‐core samples. The output of pass‐through measurement is smoothed and distorted due to convolution of magnetization with the magnetometer sensor...
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Mathematical Formalization and Algorithmization of the Main Modules of Organizational and Technical Systems
Veröffentlicht 2020-09-01“… In this regard, the key aspect of the work is to study the optimal algorithms for evaluating the state of processes occurring in the organizational and technical systems and develop on this basis the principles of mathematical formalization and algorithmization of the status assessment module. …”The purpose of the research is to develop a generalized structural scheme of organizational and technical systems based on the general theory of management, which contains the necessary and sufficient number of modules and formalize on this basis the main management tasks that act as goals of the be...
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Estimation of performance measures in a novel M/M/1 queueing model with reverse balking: A simulation-based approach
Veröffentlicht 2025-09-01“… We use a simulation-based approach to estimate key performance measures, including traffic intensity, average system size and average queue length of the proposed model using both classical and Bayesian approaches. In the classical approach, we used the Maximum Likelihood (ML) Estimation procedure to estimate the parameters using the Metropolis-Hastings (MH) algorithm. …”This article introduces a novel M/M/1 queueing model that incorporates the concept of reverse balking, where customers are more likely to join the queue as the system size increases. Traditional queuing models often assume a constant balking rate or state-dependent balking rate where the balking rat...
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Assessment of the stock status for greenland halibut (<i>Reinhardtius hippoglossoides matsuurae</i>) in the Okhotsk Sea
Veröffentlicht 2022-07-01“… It includes the additional filtering of the JABBA model result, its refinement with stringent tuning using the algorithm of No-U-Turn sampler, and checking additional parameters on hyperstability or hypersensitivity. …”State of the greenland halibut stock in the Sea of Okhotsk fishing zone is evaluated as overfished with a high probability of 97.5 % by the index of fishable biomass, and the overfishing continued in 2021. This conclusion is based on results of double filtering the posterior parameter estimates in t...
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A novel method for distracted driving behaviors recognition with hybrid CNN-BiLSTM-AM model
Veröffentlicht 2025-06-01“… A fully connected neural network layer is applied to establish a nonlinear mapping relationship between the extracted features and driving behavior categories. Bayesian optimization algorithm is adopted to automatically optimize hyperparameters of the network so as to improve training efficiency and performance of the proposed model. …”Abstract A novel deep learning framework for recognition of distracted driving behavior is proposed in this paper. The proposed framework consists of hybrid convolutional neural network and bidirectional long short term memory network to extract multi-scale spatiotemporal features of high-dimensiona...
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Calibration and Uncertainty Analysis of Freundlich and Langmuir Isotherms Using the Markov Chain Monte Carlo (MCMC) Approach
Veröffentlicht 2024-10-01“… The Metropolis algorithm’s runtime was 5.8 times that of the Gibbs algorithm. …”Organic pollutants, such as dyes, widely used in textile, dyeing, and chemical industries, pose significant risks to human health and the environment if introduced into water resources. In modeling the transport of dissolved pollutants, three processes are commonly considered: advection, dispersion,...
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Augmenting Naïve Bayes Classifiers with <i>k</i>-Tree Topology
Veröffentlicht 2025-07-01“… In addition, while in general finding a maximum spanning <i>k</i>-tree is NP-hard for fixed <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>k</mi><mo>≥</mo><mn>2</mn></mrow></semantics></math></inline-formula>, this work shows that the approximation problem can be solved in time <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mo>(</mo><msup><mi>n</mi><mrow><mi>k</mi><mo>+</mo><mn>1</mn></mrow></msup><mo>)</mo></mrow></semantics></math></inline-formula> if the spanning <i>k</i>-tree also desires to retain a given Hamiltonian path in the graph. Therefore, this algorithm can be employed to ensure efficient approximation of Bayesian networks with <i>k</i>-tree augmented Naïve Bayesian classifiers of the guaranteed minimum loss of information. …”The Bayesian network is a directed, acyclic graphical model that can offer a structured description for probabilistic dependencies among random variables. As powerful tools for classification tasks, Bayesian classifiers often require computing joint probability distributions, which can be computatio...
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Optimized AI and IoT-Driven Framework for Intelligent Water Resource Management
Veröffentlicht 2025-01-01“… The architecture combines the ensemble-learning algorithms (XGBoost, LightGBM), hybrid AIs (XGBoost + Autoencoder), and metaheuristic feature selection (GA, PSO, SA) for making intelligent decisions. …”The scheme of water resources management is necessary for reducing water scarcity in arid areas and improving water availability in general. However, water leak detection and irrigation scheduling traditional AI models are often computationally intensive and require complex hyperparameter tuning, ma...
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Improving Modularity Regularization Techniques for Estimating Structures in Complex Network
Veröffentlicht 2025-07-01VolltextComplex systems in the real world have networks differ significantly from random graphs and have non-trivial structures. In fact, they have a community structure that needs to be recognized and recovered. The stochastic block models (SBMs) are popular models for community detection in networks, whe...
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Energy Optimisation of Industrial Limestone Grinding Using ANN
Veröffentlicht 2025-07-01“… In the next phase, black-box optimisation was performed using Bayesian and genetic algorithms to identify optimal mill operating settings. …”This paper presents methods for modelling and optimising the industrial limestone grinding process carried out using a real limestone plant. Two key process evaluation indicators were developed: specific electric energy consumption and an extended indicator that also includes gas usage. Using proces...
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Comparative analysis of efficacy of different combination therapies of α-receptor blockers and traditional Chinese medicine external therapy in the treatment of chronic prostatitis...
Veröffentlicht 2023-01-01“… Therefore, based on Bayesian algorithm, a network meta-analysis was conducted by us to make a comparison between different combination therapies of α-RBs and traditional Chinese medicine external therapy. …”<h4>Background</h4>Combination therapy of α-receptor blockers (α-RBs) and traditional Chinese medicine external therapy can serve as a treatment of chronic prostatitis/chronic pelvic pain syndrome (CP/CPPS). α-RBs includes tamsulosin, terazosin and so on and the traditional Chinese medic...
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Pareto-optimal solutions of the inverse gravimetric problem in the class of three-dimensional contact surfaces
Veröffentlicht 2020-12-01“… Also, the algorithm is resistant to falling into local minima, since it uniformly explores the parametric space. …”In geophysical inverse problems, there are two approaches to data inversion. The first is the search for a number of unknowns by minimizing the residual function. The second is through probabilistic modeling of the posteriori of the probability density function in the framework of the Bayesian inte...
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Edge-Fog Computing-Based Blockchain for Networked Microgrid Frequency Support
Veröffentlicht 2025-01-01“… The parameters and hyperparameters of the LSTM-MFPC are optimized using the Bayesian Adaptive Direct Search (BADS) algorithm. …”Microgrids have gained increasing adoption in recent years due to the growing demand for renewable energy integration. Frequency support has become a critical issue in networked microgrid operation, primarily due to the intermittent nature of renewable energy sources and the inherently low system in...
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Human-Centric IoT-Driven Digital Twins in Predictive Maintenance for Optimizing Industry 5.0
Veröffentlicht 2025-06-01“… The framework uses an enhanced particle swarm optimization (PSO) algorithm to reconcile competing goals, including maintaining operator safety, optimizing asset reliability, and minimizing maintenance costs. …”Predictive maintenance now heavily relies on digital twins and the Internet of Things (IoT), which allow industrial assets to be monitored and decisions made in real time. However, adding human components to conventional optimization processes creates new difficulties as Industry 5.0 moves toward hu...
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An explainable AI-based framework for predicting and optimizing blast-induced ground vibrations in surface mining
Veröffentlicht 2025-09-01“… This study proposes a novel hybrid artificial intelligence (AI) framework that integrates physics informed neural networks (PINNs) with conventional machine learning (ML) algorithms for the accurate prediction and optimization of BIGV. …”Blast induced ground vibrations (BIGV) pose critical challenges in surface mining, threatening structural integrity, worker safety, and environmental compliance. This study proposes a novel hybrid artificial intelligence (AI) framework that integrates physics informed neural networks (PINNs) with co...
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Stacking ensemble learning framework for predicting tribological properties and optimal additive ratios of amide-based greases
Veröffentlicht 2025-07-01“… Based on the tribological experimental data, the synthetic minority oversampling technique (SMOTE) was utilized for data augmentation, and a stacking ensemble algorithm with Bayesian optimization of hyperparameters was used to construct a predictive model for tribological performance. …”This study employs a stacking ensemble learning framework to establish a regression model for predicting the tribological properties of amide-based lubricating grease and determining the optimal additive ratios. Melamine cyanuric acid (MCA) was selected as the thickener, and three extreme-pressure a...
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Analysis of informativeness of features of classification of dangerous weather events based on radar observation results
Veröffentlicht 2024-07-01VolltextOne of the crucial factors affecting the safety and regularity of state and civil aviation flights is the meteorological situation. The European territory of Russia is most characterized by dangerous meteorological phenomena associated with cumulonimbus clouds: shower, thunderstorms, hail, accompani...
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IT Diagnostics of Parkinson’s Disease Based on the Analysis of Voice Markers and Machine Learning
Veröffentlicht 2023-06-01“… After that, the object was selected using the PCA algorithm. The model was trained using the Knn and Random Forest algorithms, as well as the Bayesian neural network. …”The results of studying the parameters of the spectra of speech signals by machine learning with the use of neural networks are presented. This study was carried out in order to confirm experimentally the possibility of performing an assessment of these parameters for the detection of Parkinson’s di...
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