Denoising of Inflow of Pingzhai Reservoir Based on Fusion Algorithm of Wavelet Transform and Savitzky-Golay Filter by GAO Lin, SONG Jinwei, LI Zuoxiao

“…According to the results, compared with the five point three order smoothing method, sliding average method, and wavelet threshold denoising method, the wavelet transform SG filtering fusion algorithm significantly improves the smoothness and denoising effect while ensuring the characteristics of the reverse flow peak information of the inflow. …”
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Denoising of Inflow of Pingzhai Reservoir Based on Fusion Algorithm of Wavelet Transform and Savitzky-Golay Filter by GAO Lin, SONG Jinwei, LI Zuoxiao

“…According to the results, compared with the five point three order smoothing method, sliding average method, and wavelet threshold denoising method, the wavelet transform SG filtering fusion algorithm significantly improves the smoothness and denoising effect while ensuring the characteristics of the reverse flow peak information of the inflow. …”
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Novel algorithm for multifocus image fusion: integration of convolutional neural network and partial differential equation by Gargi J Trivedi, Rajesh Sanghvi

“…Furthermore, we aim to enhance our approach by incorporating machine learning techniques to optimize the parameters of the image fusion algorithm. …”
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A mathematical PAPR estimation of OTFS network using a machine learning SVM algorithm by Arun Kumar, Nishant Gaur, Aziz Nanthaamornphong

“…The article presents a Support Vector Machine (SVM) algorithm to lower the peak-to-average power ratio (PAPR) in networks that work in orthogonal time frequency space (OTFS). …”
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Mathematical Background and Algorithms of a Collection of Android Apps for a Google Play Store Page by Roland Szabo

“…The first application unveils an innovative SMS messaging system that substitutes manual typing with voice interaction. The key algorithm facilitates real-time conversion from speech to text for message creation and from text to speech for message playback, thus turning SMS communication into an audio-focused exchange while preserving conventional messaging standards. …”
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Vehicular cache nodes selection algorithm under load constraint in C-V2X by Zhexin XU, Kaimeng GAO, Wenkang JIA, Yi WU

“…In order to solve the problem that the C-V2X vehicle topology in urban environment was highly dynamic and the load capacity of vehicle nodes was limited, and improve the utilization of vehicular cache resources and reduce the load of base station, a vehicle cache nodes selection algorithm under load constraints was proposed.Firstly, by defining the link stability metric, the predicted weight adjacency matrix was constructed to describe the vehicular micro-topology in essence.Next, the objective function was further constructed under the load constraints and non-overlapping coverage constraint, which maximized the average link weight of the clusters by using the least cache nodes.Finally, the greedy concept was then introduced and the node states were reasonably defined.As a result, the minimum dominating set of the vehicle topology was figured out under the load constraints.Besides, the serviced neighbor nodes were then determined preferentially.The simulation results show that the proposed algorithm is close to the global optimal results in terms of the number of cache nodes and the average weight of cluster links.Moreover, the repeated response ratio of the proposed algorithm is always zero while the request response ratio can achieve the theoretical upper bound.Furthermore, the response times of cache resources can be also effectively improved.…”
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Landslide spatial prediction using data-driven based statistical and hybrid computational intelligence algorithms by Xia Zhao, Wei Chen, Paraskevas Tsangaratos, Ioanna Ilia, Qingfeng He

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Modeling and Evolutionary Optimization on Multilevel Production Scheduling: A Case Study by Ruifeng Shi, Chunxia Shangguan, Hong Zhou

“…An integrated model, which can cope with the whole multilevel scheduling information simultaneously, is proposed in this paper, and a specific evolutionary algorithm is designed to solve the integrated model with a twin-screw coding strategy. …”
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Short-Term Electric Load Forecasting for an Industrial Plant Using Machine Learning-Based Algorithms by Oğuzhan Timur, Halil Yaşar Üstünel

“…The integration of calendar, meteorological, and lagging electrical variables, along with machine learning-based algorithms, is employed to boost forecasting accuracy and optimize energy utilization. …”
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Simulation of a scalable corridor waning radiance system using fuzzy PID and genetic algorithm by Abdallah Awamu, Jimmy Nabende Wanzala, Michael Robson Atim, Cosmos Dumba

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Data-Driven Identification of Gas Turbine Engine Dynamics via Koopman Operator Genetic Algorithm by David Grasev

“…A novel application of genetic algorithm is proposed with a specifically crafted objective function that allows a constrained nonconvex optimization of functions in the Koopman observable subspace while forcing the solution to satisfy specified performance requirements via penalization. …”
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A Novel Loss Minimization Algorithm for the 3-Port Converter in a Multi-Subgrid Microgrid by Rajarshi Basu, Mahesh Kumar Mishra

“…Among them, the 3-port converter, previously proposed by the authors, optimizes the integration of different microgrid entities while minimizing the switch count. …”
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Significance of Machine Learning-Driven Algorithms for Effective Discrimination of DDoS Traffic Within IoT Systems by Mohammed N. Alenezi

“…Findings revealed that the RF model outperformed other models by delivering optimal detection speed and remarkable performance across all evaluation metrics, while KNN (K = 7) emerged as the most efficient model in terms of training time.…”
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Lightweight Transformer traffic scene semantic segmentation algorithm integrating multi-scale depth convolution by Gang XIE, Quanyi WANG, Xinlin XIE, Jian’an WANG

“…Aiming at the problems of discontinuous segmentation of thin strip objects that were easy to blend into the surrounding background and a large number of model parameters in the semantic segmentation algorithm of traffic scenes, a lightweight Transformer traffic scene semantic segmentation algorithm integrating multi-scale depth convolution was proposed.First, a multi-scale strip feature extraction module (MSEM) was constructed based on deep convolution to enhance the representation ability of thin strip target features at different scales.Secondly, a spatial detail auxiliary module (SDAM) was designed using the convolutional inductive bias feature in the shallow network to compensate for the loss of deep spatial detail information to optimize object edge segmentation.Finally, an asymmetric encoding-decoding network based on the Transformer-CNN framework (TC-AEDNet) was proposed.The encoder combined Transformer and CNN to alleviate the loss of detail information and reduce the amount of model parameters; while the decoder adopted a lightweight multi-level feature fusion design to further model the global context.The proposed algorithm achieves the mean intersection over union (mIoU) of 78.63% and 81.06% respectively on the Cityscapes and CamVid traffic scene public datasets.It can achieve a trade-off between segmentation accuracy and model size in traffic scene semantic segmentation and has a good application prospect.…”
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Dynamic Analysis and Efficient Numerical Algorithm for Rocking Response of Freestanding Packages Under Transportation Excitations by Zhenmin Qi, Dapeng Zhu

“…This approach partitions the solution into smooth intervals between impacts, significantly improving computational efficiency while maintaining accuracy. Experimental validation under sinusoidal and numerical analysis with random excitations confirms the algorithm’s effectiveness in predicting rocking behavior. …”
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A Review of Hybrid Vehicles Classification and Their Energy Management Strategies: An Exploration of the Advantages of Genetic Algorithms by Yuede Pan, Kaifeng Zhong, Yubao Xie, Mingzhang Pan, Wei Guan, Li Li, Changye Liu, Xingjia Man, Zhiqing Zhang, Mantian Li

“…When combined with other optimization techniques, genetic algorithms can augment the optimization potential for tackling complex tasks. …”
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An Uncertainty-Aware Lane Change Motion Planning Algorithm Based on Probabilistic Trajectory Prediction Distribution by Zhiqiang Zhang, Lei Zhang, Mingqiang Wang, Cong Wang, Zhenpo Wang

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Intra-Net Cognitive Radio Intelligent Utility Maximization using Adaptive PSO-Gradient Algorithm by Imran Ullah Khan

“…The performance of proposed algorithm is remarkable. …”
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VRU-YOLO: A Small Object Detection Algorithm for Vulnerable Road Users in Complex Scenes by Yunxiang Liu, Yuqing Shi

“…Additionally, a lightweight Optimized Shared Detection Head (OSDH-Head) is introduced, reducing computational complexity while improving detection efficiency. …”
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Heuristic Algorithms for the Heterogeneous Vehicle Routing Problem With Time Windows, Customers Priority, Pickup and Delivery by Moayad Tanash, Rami As'Ad

“…Both heuristics possess a two-phase structure, where the first phase yields highly prudent initial solutions employing a Greedy Randomized Adaptive Search Procedure (GRASP) in the first heuristic, and Priority-Based Ant Colony Optimization (PBACO) in the second heuristic. As for the second phase, both heuristics embrace a common Variable Neighborhood Search (VNS) algorithm that explores seven different neighborhoods to improve upon the initial solutions. …”
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