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221
Low-carbon economic optimization for flexible DC distribution networks based on the hiking optimization algorithm
Published 2025-03-01“…This leads to improved optimization accuracy, further validating its effectiveness in IES optimization.…”
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222
Path Planning of Intelligent Mobile Robots with an Improved RRT Algorithm
Published 2025-03-01“…Addressing issues such as pronounced randomness, low search efficiency, inefficient utilization of effective points, suboptimal path smoothness, and potential deviations from the optimal path in the RRT algorithm based on random sampling, we proposed an optimization algorithm that integrates Kalman filtering to eliminate redundant points along the path. …”
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223
Impact of Network Configuration on Hydraulic Constraints and Cost in the Optimization of Water Distribution Networks
Published 2025-03-01“…Further, a new approach based on the Coral Reef Algorithm (CRA) is developed and implemented to improve the technical and economic viability of the designed WDNs. …”
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224
Multi-clustering algorithm based on improved tensor chain decomposition
Published 2025-06-01“…The innovations were mainly reflected in two aspects: firstly, a new tensor decomposition framework was proposed, which effectively reduced the storage cost and improved the computational efficiency by optimizing the objective function; secondly, the improved tensor decomposition technique was applied to three main multi-clustering algorithms, including self-weighted multi-view clustering (SwMC), latent multi-view subspace clustering (LMSC), and multi-view subspace clustering with intactness-aware similarity (MSC IAS), which significantly improved the accuracy and efficiency of clustering. …”
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225
Nighttime Vehicle Detection Algorithm Based on Improved YOLOv7
Published 2025-01-01“…The Soft-EloU-NMS post-processing algorithm is further proposed to effectively reduce the leakage detection rate of dense small targets by fusing the multi-dimensional evaluation of overlap, center distance and aspect ratio. …”
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226
Renewable energy forecasting using optimized quantum temporal model based on Ninja optimization algorithm
Published 2025-04-01“…Abstract Artificial intelligence allows improvements in renewable energy systems by increasing efficiency while enhancing reliability and reducing costs. …”
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227
Well Pattern optimization as a planning process using a novel developed optimization algorithm
Published 2024-11-01“…The novelty of this work is the integrated algorithm, which improves searching performance by leveraging the memorizing characteristics of the particle swarm optimization algorithm to enhance genetic algorithm efficiency. …”
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228
Multi strategy Horned Lizard Optimization Algorithm for complex optimization and advanced feature selection problems
Published 2025-06-01“…However, when applied to high-dimensional datasets characterized by a vast number of features and limited samples-these methods often suffer from performance degradation and increased computational costs. The Horned Lizard Optimization Algorithm (HLOA) is a nature-inspired metaheuristic that mathematically mimics the adaptive defense mechanisms of horned lizards, including crypsis, skin color modulation, blood-squirting, and escape movements. …”
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229
Offshore Wind Farm Layout Optimization Considering the Power Collection System Cost
Published 2022-08-01“…The change in the size and shape of the boundaries of the wind farm site resulted in an increase in the estimated electricity generation by 2.3 % and a decrease in its cost by 4 %. When optimizing the layout of wind turbines within the fixed boundaries of the site, these indicators are improved by only 1 and 2 % as compared to the original scheme.…”
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230
Time-Dependent Multi-Center Semi-Open Heterogeneous Fleet Path Optimization and Charging Strategy
Published 2025-03-01“…The self-organizing mapping network method is employed to initialize the EV routing, and an improved adaptive large neighborhood search (IALNS) algorithm is developed to solve the optimization problem. …”
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231
Robust reinforcement learning algorithm based on pigeon-inspired optimization
Published 2022-10-01“…Reinforcement learning(RL) is an artificial intelligence algorithm with the advantages of clear calculation logic and easy expansion of the model.Through interacting with the environment and maximizing value functions on the premise of obtaining little or no prior information, RL can optimize the performance of strategies and effectively reduce the complexity caused by physical models .The RL algorithm based on strategy gradient has been successfully applied in many fields such as intelligent image recognition, robot control and path planning for automatic driving.However, the highly sampling-dependent characteristics of RL determine that the training process needs a large number of samples to converge, and the accuracy of decision making is easily affected by slight interference that does not match with the simulation environment.Especially when RL is applied to the control field, it is difficult to prove the stability of the algorithm because the convergence of the algorithm cannot be guaranteed.Considering that swarm intelligence algorithm can solve complex problems through group cooperation and has the characteristics of self-organization and strong stability, it is an effective way to be used for improving the stability of RL model.The pigeon-inspired optimization algorithm in swarm intelligence was combined to improve RL based on strategy gradient.A RL algorithm based on pigeon-inspired optimization was proposed to solve the strategy gradient in order to maximize long-term future rewards.Adaptive function of pigeon-inspired optimization algorithm and RL were combined to estimate the advantages and disadvantages of strategies, avoid solving into an infinite loop, and improve the stability of the algorithm.A nonlinear two-wheel inverted pendulum robot control system was selected for simulation verification.The simulation results show that the RL algorithm based on pigeon-inspired optimization can improve the robustness of the system, reduce the computational cost, and reduce the algorithm’s dependence on the sample database.…”
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232
Building Construction Design Based on Particle Swarm Optimization Algorithm
Published 2022-01-01“…When the constraint cost was 320,000 yuan, the global optimal risk loss and global optimal control cost were 910,100 yuan and 317,300, yuan respectively. …”
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233
An Improved SLIC Superpixel Segmentation Algorithm Combined with FPGA Technology
Published 2020-02-01“…In view of the large amount of calculations, complexity of algorithm and the implementation is slow The paper combines superpixel segmentation technology with FPGA parallel processing technology, and puts forward a method to realize the image segmentation algorithm on FPGA platform SLIC is a kind of fast image segmentation algorithm SLIC has a lot of improvements in efficiency, costing and segmentation results compared with traditional image segmentation algorithm On the basis of the principle of SLIC segmentation algorithm, we made a further improvement algorithm by optimizing the operation and extracting a small number of pixels of the original image to reduce computational complexity Finally, the last of the original image segmentation was achieved by K nearest neighbor classification process We completed the algorithm design on FPGA platform The simulation results show that the improved algorithm has a better segmentation results and the processing speed has about 40% promotion And the improved algorithm has a higher realtime performance…”
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234
Optimization of machine learning algorithms for proteomic analysis using topsis
Published 2022-11-01“…The present study focuses on a new application of the TOPSIS method for the optimization of machine learning algorithms, supervised neural networks (SNN), the quick classifier (QC), and genetic algorithm (GA) for proteomic analysis. …”
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235
(IoT) Network intrusion detection system using optimization algorithms
Published 2025-07-01“…Abstract To address the complex requirements of network intrusion detection in IoT environments, this study proposes a hybrid intelligent framework that integrates the Whale Optimization Algorithm (WOA) and the Grey Wolf Optimization (GWO) algorithm—referred to as WOA-GWO. …”
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236
ALGORITHM FOR OPTIMIZING ORGANIC CARBON AND NITROGEN FLOWS ON RECLAIMED LANDS
Published 2024-11-01Get full text
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237
GNN-based optimization algorithm for joint user scheduling and beamforming
Published 2022-07-01“…The coordinated multi-point (CoMP) transmission technology has the characteristics of reducing co-channel interference and improving spectral efficiency.For the CoMP technology, user scheduling (US) and beamforming (BF) design are two fundamental research problems located in the media access control layer and the physical layer, respectively.Under the consideration of user service quality requirements, the joint user US-BF optimization problem was investigated with the goal of maximizing network throughput.To overcome the problem that the traditional optimization algorithm had high computational cost and couldn’t effectively utilize the network historical data information, a joint US and power allocation (M-JEEPON) model based on graph neural network was proposed to realize joint US-BF optimization by combining the beam vector analytical solution.The simulation results show that the proposed algorithm can achieve the performance matching or even better than traditional optimization algorithms with lower computational overhead.…”
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238
Applying Genetic Algorithm for test pattern generation process optimization
Published 2024-04-01Get full text
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239
DEVELOPMENT OF THE ALGORITHM FOR CHOOSING THE OPTIMAL SCENARIO FOR THE DEVELOPMENT OF THE REGION'S ECONOMY
Published 2018-04-01“…It was found that the rationale and choice of the optimal scenario is an important stage in the development of the sustainable development program of the regional economy, since it helps to quantify the most probable trajectories of changes in the activities of all participants in the region's economy.Conclusions and Relevance: the practical significance of the developed algorithm lies in the possibility of using it to improve the stability of the development of the economy of specific regions. …”
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240
A binary grasshopper optimization algorithm for solving uncapacitated facility location problem
Published 2025-05-01“…The Uncapacitated Facility Location Problem (UFLP) is a real-world binary optimization problem that aims to find the number of facilities to open, minimizing the total cost of exchange between customers and facilities, as well as the opening costs of these facilities. …”
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