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161
Elimination of defects in photos using neural networks
Published 2023-01-01“…To solve such a problem, it is necessary to develop algorithms for searching and recognizing defects in photographs, as well as algorithms for eliminating these defects using the mathematical apparatus of a neural network.The article discusses approaches to the development of a neural network for recognizing defects in photographs with their subsequent restoration.Conclusion. …”
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162
Flood Forecasting for Small Reservoirs Based on Neural Networks
Published 2023-01-01“…In flood forecasting,empirical prediction methods report low accuracy,and traditional hydrological models face the problems of large workloads and difficult promotion when they are applied to small reservoirs.Hence,an artificial neural network (ANN) method is introduced,which is equipped with powerful feature-learning capability.It is combined with the genetic algorithm (GA) to find the optimal parameters for flood forecasting of small reservoirs as GA can realize automatic optimization of the time step and hidden-layer neuron nodes in ANN.In this way,parameter search can be targeted,and personalized flood forecasting models can be constructed for each small reservoir.In addition,the flood forecasting models based on the back propagation (BP),long short-term memory (LSTM),and gated recurrent unit (GRU) neural networks are built,and comparisons between simulations and measured data are conducted for the flood process.The results show that the LSTM model has high prediction accuracy and good stability and can learn and simulate the water-level change pattern of the actual flood process,demonstrating better prediction performance than BP and GRU models.…”
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163
Differential diagnosis in joint and spine damages
Published 2020-05-01“…Attention is paid to the semiotics of joint damage and extra-articular manifestations in various rheumatic diseases. A brief algorithm for a differential diagnostic search for joint pain is given.…”
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164
The LETBP feature descriptor based fish species classification using Kepler optimization with Extreme Learning Machine
Published 2025-03-01“…The ELM network randomly selects the bias and weights and in order to overcome this issue an optimization technique called Kepler Optimization Algorithm (KOA) is adopted. The KOA algorithm tries to improve the search space of exploration and exploitation ratio. …”
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165
Development of an imitation learning method for a neural network system of mobile robot’s movement on example of the maze solving
Published 2024-09-01“…It was proven that, thanks to the proposed method of imitative learning, the student agent is able not only to adopt the required behavior patterns from the expert agent – to search for an exit in a previously unknown labyrinth using the right-hand algorithm, but also to independently acquire new ones (changing speed on a turn, bypassing small dead-end corridors), which positively influence the performance of the assigned task.…”
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166
A Q-Learning Crested Porcupine Optimizer for Adaptive UAV Path Planning
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167
Optimizing Multi-Echelon Delivery Routes for Perishable Goods with Time Constraints
Published 2024-12-01“…In the second stage, the initial routing solution is optimized using a linear programming approach from the Ortools solver combined with an Improved Adaptive Large Neighborhood Search (IALNS) algorithm. The effectiveness of the proposed model and algorithm is validated through a case study analysis. …”
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168
Differential Diagnosis of Jejunum and Ileum Tumours Based on Video Capsule Endoscopy Data Using Mathematical Analysis
Published 2018-11-01“…The indications for VCE were a search for a reason of gastrointestinal bleeding, the anaemia of unknown etiology and suspected tumour of the small intestine. …”
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169
Optimal Allocation and Sizing of Multiple DGs with Reactive Power Capabilities in a Three-Phase Unbalanced Distribution System
Published 2024-12-01“…The DG size, node, and power factor are the coordinated control variables presented in this study to minimize the power loss. Genetic Algorithm, Pattern Search, Particle Swarm Optimization, and Grey Wolf Optimizer algorithms have been exploited in the IEEE 37 node test feeder to find the optimal location, sizes, and power factors of the DGs. …”
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170
Concrete Dam Deformation Prediction Model Based on Attention Mechanism and Deep Learning
Published 2025-01-01“…To address the multi-factor coupling, temporal dependency, and nonlinear complexity characteristics of concrete dam deformation, this paper proposed a hybrid prediction model integrating attention mechanisms, bidirectional long short-term memory (BiLSTM) networks, and sparrow search algorithm (SSA). The model comprehensively matched the multiple requirements of information weighting, temporal dependency modeling, and model optimization in concrete dam deformation prediction, forming a synergistic enhancement effect among methods.The attention mechanism operates on both feature and temporal dimensions to comprehensively enhance the model's focus on critical information. …”
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171
Reinforcement learning-based alpha-list iterated greedy for production scheduling
Published 2024-12-01“…Metaheuristics can benefit from analyzing patterns and regularities in data to perform more effective searches in the solution space. …”
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172
Optimal fractional order automatic generation control including an excitation system for hybrid interconnected grids
Published 2025-07-01“…The hybrid technique consists of two different types of algorithms: the secretary bird optimization algorithm and pattern search. …”
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173
A configuration and scheduling optimization method for integrated energy systems considering massive flexible load resources
Published 2025-03-01“…Flexible loads were categorized into three types to match different electricity consumption patterns. Additionally, an enhanced Kepler Optimization Algorithm (EKOA) was proposed, incorporating chaos mapping and adaptive learning rate strategies to improve search scope, convergence speed, and solution efficiency. …”
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174
Proposal of a new classification scheme for periocular injuries
Published 2017-01-01“…The SPOT classification has taken into account the periocular soft tissue injuries i.e., upper eyelid, lower eyelid, medial and lateral canthus injuries., based on observed clinico-anatomical patterns of eyelid injuries. Conclusion: The SPOT classification seems to be a reliable system to address eyelid injuries. …”
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175
Satellite Image Classification Using a Hybrid Manta Ray Foraging Optimization Neural Network
Published 2023-03-01“…The trained network can discover hidden data patterns in unseen data. The learning algorithm and seed selection play a vital role in the performance of the network. …”
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176
Global MPPT optimization for partially shaded photovoltaic systems
Published 2025-03-01“…From the simulation results, it was found that ChOA have shown higher conversion efficiency of 99.63% with maximum power output of 525.13 W when compared to other optimization algorithms for the given shading pattern condition. …”
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177
An Adaptive Motion Estimation Scheme for Video Coding
Published 2014-01-01“…At last, according to the MV distribution prediction results, achieve self-adaptive subregional searching by the new estimation search patterns. Experimental results show that more than 50% of total search points are dramatically reduced compared to the UMHexagonS algorithm in JM 18.4 of H.264/AVC. …”
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178
A Systematic Study on the Extraction and Image Reproduction of Ceramic Sculpture Artworks
Published 2022-01-01“…In order to solve the research on the extraction of ceramic sculpture artwork patterns, and, in the process of image reproduction, the problem of too few feature points in the object image, the author proposes an image stitching algorithm that combines SIFT and MSER algorithms. …”
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179
Fishing for biomarkers: analyzing mass spectrometry data with the new ClinProTools™ software
Published 2005-06-01“…Additionally, it is necessary to apply statistical analysis and pattern matching algorithms to attain validated signal patterns that may allow for later applications in sample classification. …”
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180
Research on Anomaly Detection Model for Power Consumption Data Based on Time-Series Reconstruction
Published 2024-09-01“…Points with large residuals are considered outliers, as they significantly differ from the normal pattern. The detection module employs a random forest algorithm optimized by grid search to detect residuals and ultimately identify outliers. …”
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