SynthSecureNet: An Improved Deep Learning Architecture with Application to Intelligent Violence Detection by Ntandoyenkosi Zungu, Peter Olukanmi, Pitshou Bokoro

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Review on algorithms of dealing with depressions in grid DEM by Yi-Jie Wang, Cheng-Zhi Qin, A-Xing Zhu

“…Existing ways of improving the computation efficiency of depression-processing algorithms are also presented, i.e. serial algorithm optimization and parallel algorithms. …”
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YOLO-AMM: A Real-Time Classroom Behavior Detection Algorithm Based on Multi-Dimensional Feature Optimization by Yi Cao, Qian Cao, Chengshan Qian, Deji Chen

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Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques by Rabiu Aminu, Samantha M. Cook, David Ljungberg, Oliver Hensel, Abozar Nasirahmadi

“…The concept of explainable artificial intelligence was adopted by incorporating permutation feature importance ranking and Shapley Additive explanations values to identify the feature set that optimized a model's performance while reducing computational complexity. …”
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Bus Arrival Time Prediction Using Wavelet Neural Network Trained by Improved Particle Swarm Optimization by Yuanwen Lai, Said Easa, Dazu Sun, Yian Wei

“…Accurate prediction can help passengers make travel plans and improve travel efficiency. Given the nonlinearity, randomness, and complexity of bus arrival time, this paper proposes the use of a wavelet neural network (WNN) model with an improved particle swarm optimization algorithm (IPSO) that replaces the gradient descent method. …”
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A Recommendation Algorithm Based on Restricted Boltzmann Machine by WANG Weibing, ZHANG Lichao, XU Qian

“…In the case where the amount of data is too large, the recommended results output by the RBM model will be broader Besides, many collaborative filtering algorithms currently do not handle large data sets better So, we try to use the deep learning technology to strengthen the personalized recommendation model We propose a hybrid recommendation model combining the bound Boltzmann model and the hidden factor model First, we use the RBM algorithm to generate candidate sets, and score the sparse matrix of the candidate set Then we use the LFM model to sort the candidate results and select the optimal solution for recommendation The hybrid model is validated using used large public datasets It can be seen from the verification that compared with the traditional recommendation model, the proposed method can improve the accuracy of the score prediction…”
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Optimisation of the adaptive neuro-fuzzy inference system for adjusting low-cost sensors PM concentrations by Martina Casari, Piotr A. Kowalski, Laura Po

“…The paper also explores various ANFIS configurations, including two distinct optimization algorithms, and investigates the impact of the number and type of membership functions on the fuzzy system's performance. …”
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Passivity-Based Control for Rocket Launcher Position Servo System Based on ADRC Optimized by IPSO-BP Algorithm by Rong-lin Wang, Bao-chun Lu, Yuan-long Hou, Qiang Gao

“…Furthermore, to improve the learning capability, the improved PSO algorithm is adopted to optimize the learning rates of the back propagation neural networks. …”
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Optimizing the neural network and iterated function system parameters for fractal approximation using a modified evolutionary algorithm by Sana Abdulla, K. Mahipal Reddy

“…In this study, we propose an evolutionary optimization strategy to enhance the accuracy and adaptability of RFC splines by optimizing their scaling factor and shape parameters using our novel Fractal Differential Evolution (FDE) algorithm. …”
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An improved synergistic dual-layer feature selection algorithm with two type classifier for efficient intrusion detection in IoT environment by G Logeswari, K Thangaramya, M Selvi, J. Deepika Roselind

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Integrating Genetic Algorithm and Geographically Weighted Approaches into Machine Learning Improves Soil pH Prediction in China by Wantao Zhang, Jingyi Ji, Binbin Li, Xiao Deng, Mingxiang Xu

“…This study integrates Geographic Weighted Regression (GWR) with three ML models (Random Forest, Cubist, and XGBoost) and designs and develops three geographically weighted machine learning models optimized by Genetic Algorithms to improve the prediction of soil pH values. …”
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Evaluation and Improvement of Ocean Color Algorithms for Chlorophyll-<i>a</i> and Diffuse Attenuation Coefficients in the Arctic Shelf by Yubin Yao, Tao Li, Qing Xu, Xiaogang Xing, Xingyuan Zhu, Yubao Qiu

“…The proposed OCx-AS series for Chl-<i>a</i> and <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>Κ</mi></mrow><mrow><mi mathvariant="normal">d</mi></mrow></msub></mrow></semantics></math></inline-formula>-DAS models for <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>Κ</mi></mrow><mrow><mi mathvariant="normal">d</mi></mrow></msub><mo>(</mo><mi>λ</mi><mo>)</mo></mrow></semantics></math></inline-formula> significantly reduce retrieval errors, achieving RMSE improvements of over 50% relative to global standard algorithms. …”
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An explainable AI-based framework for predicting and optimizing blast-induced ground vibrations in surface mining by Charan Kumar Ala, Zefree Lazarus Mayaluri, Aman Kaushik, Nikhat Parveen, Surabhi Saxena, Abu Taha Zamani, Debendra Muduli

“…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. …”
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Optimal D-STATCOM placement and sizing using a novel bird swarm operated exploitation of elephant herd algorithm by V. Tejaswini, D. Susitra

“…In the 33-bus system at hour 14, the BSOEEH model achieved optimal results, surpassing established methods by significant margins: 1.06% superior to Grey Wolf Optimizer (GWO), 1.02% superior to Whale Optimization Algorithm (WOA), 1.02% superior to the GWO-WOA hybrid model, 0.13% superior to Elephant Herding Optimization (EHO), and 0.93% superior to Backtracking Search Algorithm (BSA). …”
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An integrated stacked convolutional neural network and the levy flight-based grasshopper optimization algorithm for predicting heart disease by Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi, Majad Mansoor, Filippo Sanfilippo

“…This study proposes a novel hybrid model integrating a Stacked Convolutional Neural Network (SCNN) with the Levy Flight-based Grasshopper Optimization Algorithm (LFGOA) to address this challenge. …”
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Enhanced Prediction and Evaluation of Hydraulic Concrete Compressive Strength Using Multiple Soft Computing and Metaheuristic Optimization Algorithms by Tianyu Li, Xiamin Hu, Tao Li, Jie Liao, Lidan Mei, Huiwen Tian, Jinlong Gu

“…In the initial stage, several classic machine learning models are selected as base models, and the optimal parameters of these models are obtained using the improved metaheuristic-based gray wolf algorithm. …”
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A bi-subpopulation coevolutionary immune algorithm for multi-objective combinatorial optimization in multi-UAV task allocation by Xi Chen, Yu Wan, Jingtao Qi, Zipeng Zhao, Yirun Ruan, Jun Tang

“…Therefore, this paper constructs a Multi-objective Combinatorial Optimization in Multi-UAV Task Allocation Problem (MCOTAP) model, and proposes a Bi-subpopulation Coevolutionary Immune Algorithm (BCIA). …”
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A combined improved dung beetle optimization and extreme learning machine framework for precise SOC estimation by Kaihua Yao, Xinyu Yan, Xiling Mao, Mengwei Li, Xiao Li, Ziyu Lian, Yuxiang Han

“…The novelty of the model stems from the application of the IDBO algorithm, which incorporating Circle chaotic mapping, the Golden sine strategy, and the Levy flight strategy, for hyper-parameter optimization. …”
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Bio-Inspired Multiobjective Optimization for Designing Content Distribution Networks by Gerardo Goñi, Sergio Nesmachnow, Diego Rossit, Pedro Moreno-Bernal, Andrei Tchernykh

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Identifying influential spreaders based on improving communication transmission model and network structure by Shimeng Zhang, Zejun Sun, Guan Wang, Haifeng Hu, Feifei Wang, Xiaoyan Sun

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