Machine learning algorithm for intelligent detection of WebShell by Hua DAI, Jing LI, Xin-dai LU, Xin SUN

“…WebShell is a common tool for network intrusions,which has the characteristics of great harm and good concealment.The current detection method is relatively simple,and easy to be bypassed,so it is difficult to deal with complex and flexible WebShell.To solve these problems,a supervised machine learning algorithm was put forward to detect WebShell intelligently.By learning the features of existing WebShell and non-existing WebShell pages,the algorithm can make prediction of the unknown pages,and the flexibility and adaptability were both very good.Compared with the traditional WebShell detection methods,the experiment proves that the algorithm has higher detection efficiency and accuracy,and at the same time there is a certain probability to detect new types of WebShell.…”
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Adaptive Top-K Algorithm for Medical Conversational Diagnostic Model by Yiqing Yang, Guoyin Zhang, Yanxia Wu, Zhixiang Zhao, Yan Fu

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Integration of the reptile search algorithm and the adaptive neuro-fuzzy inference system enhances standardized precipitation evapotranspiration index forecasting by Zahra Kayhomayoon, Mohammad Javad Bahmani, Sami Ghordoyee Milan, Ommolbanin Bazrafshan, Ronny Berndtsson

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Machine Learning–Driven Adaptive Testing: An Application for the MMPI Assessment by Daiana Colledani, Egidio Robusto, Pasquale Anselmi

“…This paper aims to examine the effectiveness of machine learning classification algorithms as a strategy to overcome the limitations associated with traditional methods for developing computerized adaptive versions of the Minnesota Multiphasic Personality Inventory-2 (MMPI-2). …”
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Influence of Modal Decomposition Algorithms on Nonlinear Time Series Machine Learning Prediction Models in Engineering: A Case Study of Subway Tunnel Settlement by Qingmeng Shen, Yuming Wu, Limin Wan, Qian Chen, Yue Li, Zichao Liao, Wenbo Wang, Feng Li, Tao Li, Jiajun Shu

“…First, the original data are optimized via the SSA, which has global optimization capability, high noise immunity, and high adaptivity. The original signal is subsequently decomposed into multiple subsignal sequences via a variational modal decomposition (VMD) algorithm combined with a rolling decomposition technique. …”
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A two‐stage transformer fault diagnosis method based multi‐filter interactive feature selection integrated adaptive sparrow algorithm optimised support vector machine by Hanyu Shi, Mingxia Chen

“…Therefore, this study proposes a novel two‐stage transformer fault diagnosis strategy, which includes a multi‐filter interactive feature selection method (MIFS) constructed, and a diagnosis model ASSA‐SVM based on the adaptive sparrow algorithm (ASSA) optimised support vector machine (SVM). …”
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Optimized breast cancer diagnosis using self-adaptive quantum metaheuristic feature selection by Alok Kumar Shukla, Shubhra Dwivedi, Deepak Singh, Sunil Kumar Singh, Diwakar Tripathi, Ram Kishan Dewangan

“…Most importantly, a self-adaptive genetic algorithm (GA) is also incorporated into TLBO to tradeoff between exploration and exploitation to handle slow convergence and exploitation competence, and simultaneously optimizing parameters of support vector machines (SVM) and the best features subset is our primary objective. …”
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Adaptive Particle Swarm Optimization with Landscape Learning for Global Optimization and Feature Selection by Khalil Abbal, Mohammed El-Amrani, Oussama Aoun, Youssef Benadada

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A simplified approach for efficiency analysis of machine learning algorithms by Muthuramalingam Sivakumar, Sudhaman Parthasarathy, Thiyagarajan Padmapriya

“…The efficiency of machine learning (ML) algorithms plays a critical role in their deployment across various applications, particularly those with resource constraints or real-time requirements. …”
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Fake News Detection Model Basing on Machine Learning Algorithms by Mohammed A. Taha, Haider D. A. Jabar, Widad K. Mohammed

“…This research paper relies on finding and analyzing the characteristics of the text, then the words are converted into features using TF-IDF technology, after that the highest-ranking features are identified for the purpose of studying and distinguishing the spread of news, whether it is real or fake using machine learning techniques. Finally, the Logistic Regression, Decision Tree, Gradient Boosting and Random Forest algorithm has been adapted. …”
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A Novel Approach for Evaluating Web Page Performance Based on Machine Learning Algorithms and Optimization Algorithms by Mohammad Ghattas, Antonio M. Mora, Suhail Odeh

“…This study introduces a novel evaluation framework for predicting web page performance, utilizing state-of-the-art machine learning algorithms to enhance the accuracy and efficiency of web quality assessment. …”
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Adaptive Algorithm Recommendation and Application of Learning Resources in English Fragmented Reading by Jinyu Cheng, Hong Wang

“…Then, combined with machine learning algorithms, an adaptive recommendation model of learning resources in English fragmented reading is constructed. …”
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Autonomous and adaptive congestion control for machine-type communication in cellular network by Qi Pan, Xiangming Wen, Zhaoming Lu, Wenpeng Jing, Haijun Zhang

“…In this article, we provide an autonomous and adaptive attractor-selection-based congestion control scheme for massive access from machine-type communication devices based on the resource separation scheme. …”
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Design and Experimental Testing of Holly Pruning Machine with Adaptive Adjustment Tool by Xiuhao Yu, Chengming Hou, Liqi Qiu, Xuesong Li, Penghui Yao, Ying Zhao

“…To improve the efficiency of holly pruning, effectively solve the labor intensity of manual handheld pruning machines, and the frequent replacement of tools when pruning different shapes of hollies, this study designed a pruning machine with adaptive tool adjustment. …”
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Improvement strategies for heuristic algorithms based on machine learning and information concepts: a review of the seahorse optimization algorithm by Shixing Zheng

“…Consequently, it transforms the discrete “iteration-weight” mapping ( $t\rightarrow w$t→w ) into a continuous “distance-weight” mapping ( $d\rightarrow w$d→w ), thereby enhancing the adaptability and optimization capability of the algorithm. …”
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Adaptive Remaining Capacity Estimator of Lithium-Ion Battery Using Genetic Algorithm-Tuned Random Forest Regressor Under Dynamic Thermal and Operational Environments by Uzair Khan, Mohd Tariq, Arif I. Sarwat

“…This paper proposes an adaptive estimator for the remaining capacity of lithium-ion batteries, leveraging a Genetic Algorithm (GA)-tuned random forest (RF) regressor. …”
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Improving frequency stability in grid-forming inverters with adaptive model predictive control and novel COA-jDE optimized reinforcement learning by Muhammad Zubair Yameen, Zhigang Lu, Fayez F. M. El-Sousy, Waqar Younis, Baqar Ali Zardari, Abdul Khalique Junejo

“…This research presents an Adaptive Model Predictive Control (AMPC) framework to enhance GFM performance in Virtual Synchronous Machine (VSM) mode, ensuring robust frequency stability under uncertainties. …”
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A Data-Driven Parameter Adaptive Clustering Algorithm Based on Density Peak by Tao Du, Shouning Qu, Qin Wang

“…In this paper, we propose a parameter adaptive clustering algorithm DDPA-DP which is based on density-peak algorithm. …”
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Adaptive algorithm for reducing pulse noise level in images from CCTV cameras by Andrey Sadchenko, Oleg Kushnirenko, Alexander Troyanskiy, Yurii Savchuk

“…These setbacks call for a need to develop an adaptive median filtering algorithm, which would produce a reconstructed image as a joint result of processing with median filters with different apertures. …”
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A Genetic Algorithm Approach to Adaptive Learning: Enhancing Learner Satisfaction and Performance by Anju Kalwar, Deepika Shekhawat, Sandeep Joshi, Amit Kumar Bairwa

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