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The Path Tracking Control of Unmanned Surface Vehicles Based on an Improved Non-Dominated Sorting Genetic Algorithm II-Based Multi-Objective Nonlinear Model Predictive Control Meth...
Published 2024-11-01“…This paper proposes a multi-objective nonlinear model predictive control (MOMPC) method based on an improved non-dominated sorting genetic algorithm II (NSGAII) for the path tracking problem of unmanned surface vehicles (USVs). …”
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1222
Intelligent Teaching Recommendation Model for Practical Discussion Course of Higher Education Based on Naive Bayes Machine Learning and Improved <i>k</i>-NN Data Mining Algorithm
Published 2025-06-01“…Then, relying on the student grouping, we use the matching features between the students’ interest vector and the practical topic vector to construct an intelligent teaching recommendation model based on an improved <i>k</i>-NN data mining algorithm, in which the optimal complete binary encoding tree for the discussion topic is modeled. …”
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1223
Adaptive Top-K Algorithm for Medical Conversational Diagnostic Model
Published 2024-08-01“…Additionally, the Top-K algorithm optimizes the diagnostic model through a policy network loss function, effectively reducing the number of symptoms and diseases processed and improving the system’s response speed by 1.3–1.9 times compared to the state-of-the-art differential diagnosis systems.…”
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1224
Image cluster algorithm of hybrid encoding method
Published 2017-02-01“…In the clustering analysis based on swarm intelligence optimization algorithm,the most of encoding method only used single form,and this method might be limit range of search space,the algorithm was easy to fall into local op-timum.In order to solve this problem,image clustering algorithm of hybrid encoding (HEICA) was proposed.Firstly,a hybrid encoding model based on image clustering was established,this method could expand the scope of the search space.Meanwhile,it was combined with two optimization algorithms which improved rain forest algorithm (IRFA) and quantum particle swarm optimization (QPSO),this method could improve the global search capability.In the simulation experiment,it was carried out to illustrate the performance of the proposed method based on four datasets.Compared with results form four measured cluster algorithm.The experimental results show that the algorithm has strong global search capability,high stability and clustering effect.…”
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1225
Mathematical Models for Management Information Systems on Digital Platforms: from Resource Management to Demand Forecasting
Published 2025-06-01“…The use of optimization methods, graph algorithms, forecasting, and machine learning to improve the efficiency of digital systems is investigated. …”
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1226
Technique on Vehicle Damage Assessment After Collisions Using Optical Radar Technology and Iterative Closest Point Algorithm
Published 2024-01-01“…We apply the Iterative Closest Point (ICP) algorithm and Singular Value Decomposition (SVD) methods, along with a proposed deep learning neural network optimization model, to perform point cloud alignment between the pre-collision and post-collision vehicle models. …”
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1227
A Feasibility Study of a Virtual Power Line Device to Improve Hosting Capacity in Renewable Energy Sources
Published 2025-07-01Get full text
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1228
A novel approach to intrusion detection system using hybrid flower pollination and cheetah optimization algorithm
Published 2025-04-01“…Abstract The study aims to address critical challenges in network security, particularly the limitations of traditional intrusion detection systems (IDS) in terms of adaptability, detection precision, and high false positive rates in dynamic network environments. A novel hybrid IDS model integrating the Flower Pollination Algorithm (FPA), Cheetah Optimization Algorithm (COA), and Artificial Neural Networks (ANN) is proposed to enhance detection accuracy, reduce false positives, and optimize feature selection, anomaly detection, and rule adaptation. …”
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1229
Impact of surrogate model accuracy on performance and model management strategy in surrogate-assisted evolutionary algorithms
Published 2025-09-01“…Surrogate-assisted evolutionary algorithms (SAEAs) are widely used to solve expensive optimization problems where evaluating candidate solutions is computationally intensive. …”
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1230
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1231
Research on 5G base station energy saving system based on DCNN-LSTM load prediction algorithm
Published 2023-04-01“…With the rapid construction of the 5G wireless communication network, the energy consumption pressure of operators, and even the overall communication industry, is simultaneously highlighted.Achieving sustainable development of the industry through energy conservation and consumption reduction has become a new research direction for the current 5G network development.Taking the PRB rate as the load evaluation index, LSTM model was improved by using DCNN to extract the depth feature of the cell’s indicators.A set of DCNN-LSTM deep learning model that could predict the future value of PRB rate was proposed.On the basis of the improved algorithm, the network topology of the current 5G access network was optimized.An additional network element and its working system were designed.An intelligent energy-saving system, which ensured the network experience, of 5G base stations was realized.…”
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1232
Localization of Sensor Nodes in 3D Wireless Sensor Networks with a Single Anchor by an Improved Adaptive Artificial Bee Colony (iaABC) Algorithm
Published 2025-03-01“…The method employs the Improved Adaptive Artificial Bee Colony (iaABC) algorithm, a model of the classical ABC algorithm. …”
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1233
Simultaneous Energy Optimization of Heating Systems by Multi-Zone Predictive Control—Application to a Residential Building
Published 2024-10-01“…The research methodology uses dynamic thermal simulation, parallel predictive models based on multiple linear regressions, and a multi-objective non-dominated sorting genetic algorithm II (NSGA-II) for the optimization process, which evaluates various generated heating strategies. …”
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1234
Study on Optimal Decision of Unit Commitment with Flexible Reserve Participation in Power Grid
Published 2023-06-01“…Secondly, a unit combination model considering the flexible reserve is established with the objective function of minimizing the total operating cost of the system, and the optimization algorithm program is written in the Lingo environment to optimize a variety of reserve resources. …”
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1235
Dynamic Optimization of Xylitol Production Using Legendre-Based Control Parameterization
Published 2025-05-01“…This paper presents an improved methodology for optimizing the fed-batch fermentation process of xylitol production, aiming to maximize the final concentration in a bioreactor co-fed with xylose and glucose. …”
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1236
Determination of Optimal Parameters of the Ground Filling During the Laying of Power Cable Lines
Published 2025-04-01“…Otherwise, the use of special backfills becomes impractical. To solve the optimization problem, a genetic algorithm implemented in the MS Excel environment was used. …”
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1237
A novel two-stage feature selection method based on random forest and improved genetic algorithm for enhancing classification in machine learning
Published 2025-05-01“…Then, the improved genetic algorithm is used to search for the global optimal feature subset further. …”
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1238
Research on Early Diagnosis Methods for Broiler Chicken Diseases Based on Swarm Intelligence Optimization Algorithms and Random Forest
Published 2025-06-01“…To optimize performance, we developed RF_WOA_DBO-an integrated algorithm combining RF with enhanced Whale Optimization Algorithm (WOA) for global feature selection and modified Dung Beetle Optimizer (DBO) for local parameter tuning. …”
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1239
Voltage and frequency regulation in wind penetrated deregulated power system using an electric vehicle and IPFC assisted model predictive controller
Published 2025-08-01“…The proposed controller is benchmarked against conventional PID, fractional-order PIλDF, and MPC schemes optimized via Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA). …”
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1240
An Improvement of Stochastic Gradient Descent Approach for Mean-Variance Portfolio Optimization Problem
Published 2021-01-01“…The aim is to fasten the convergence rate of the Adam algorithm. This improvement is termed as Adam with standard error (AdamSE) algorithm. …”
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