Enhancing Streamflow Prediction Accuracy: A Comprehensive Analysis of Hybrid Neural Network Models with Runge–Kutta with Aquila Optimizer by Rana Muhammad Adnan, Wang Mo, Ahmed A. Ewees, Salim Heddam, Ozgur Kisi, Mohammad Zounemat-Kermani

“…Abstract This study investigates the efficacy of hybrid artificial neural network (ANN) methods, incorporating metaheuristic algorithms such as particle swarm optimization (PSO), genetic algorithm (GA), gray wolf optimizer (GWO), Aquila optimizer (AO), Runge–Kutta (RUN), and the novel ANN-based Runge–Kutta with Aquila optimizer (LSTM-RUNAO). …”
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The Impact of Feature Extraction in Random Forest Classifier for Fake News Detection by Dhani Ariatmanto, Anggi Muhammad Rifai

“…The influence of fake news has become a pressing social problem, shaping public opinion in important events such as elections. This research focuses on detecting and classifying fake news using the Random Forest algorithm by investigating the impact of feature extraction techniques on classification accuracy, this study specifically employs the TF-IDF method. …”
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Sentiment Analysis of TIMNAS Indonesia's Participation in the Asian Cup U23 2024 on X Using Naive Bayes and SVM by Sewin Fathurrohman, Irfan Ricky Afandi, Firman Noor Hasan

“…The analysis results indicate that the SVM algorithm achieves a higher % accuracy rate of 95% compared to Naive Bayes, which achieves 87%. …”
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Stackelberg Game Based on Trajectory Prediction for Lane Change in Mixed Traffic by Baichuan Shi, Li Zhai, Chang Liu

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A Novel Approach on Decision Support System Based on the Aczel-Alsina Aggregation Operators and Their Applications to Supplier Selection Problems by Yong-Long Wang, Ebenezer Bonyah, Mashael Khayyat, Zubair Ahmad, Muhammad Shakeel, Waris Khan

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IHML: Incremental Heuristic Meta-Learner by Onur Karadeli, Kıymet Kaya, Şule Gündüz Öğüdücü

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Medical Dataset Classification: A Machine Learning Paradigm Integrating Particle Swarm Optimization with Extreme Learning Machine Classifier by C. V. Subbulakshmi, S. N. Deepa

“…This paradigm integrates the successful exploration mechanism called self-regulated learning capability of the particle swarm optimization (PSO) algorithm with the extreme learning machine (ELM) classifier. …”
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Online electric network capacity assesment by A. I. Motovilov, I. I. Solovejev

“…The aim of the work is to develop an algorithm for assessing the throughput of the electric network. …”
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A Damage Detection Approach in the Era of Industry 4.0 Using the Relationship between Circular Economy, Data Mining, and Artificial Intelligence by Meisam Gordan, Saeed-Reza Sabbagh-Yazdi, Khaled Ghaedi, Zubaidah Ismail

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Control Strategy for PHEB Based on Actual Driving Cycle with Driving Style Characteristic by Jianping Gao, Zhenhai Xu, Xiaojie Gao

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Modelling of Green function in a rectangular room based upon the geometrical-filtration model by R. Marczuk, L. Majkut

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An Inspiration Recommendation System for Automotive Styling Design Based on User Behavior Data and Group Preferences by Wanxin Cai, Mingqing Yang, Li Lin

“…Firstly, the K-means algorithm is employed to cluster users based on a variety of features. …”
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An Improved Reduced-Dimension Robust Capon Beamforming Method Using Krylov Subspace Techniques by Xiaolin Wang, Xihai Jiang, Yaowu Chen

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Analysis of communication data of mobile terminal based on protocol reversal by Mingyuan ZHANG, Xinyu QI, Yubo SONG, Rongrong GU, Aiqun HU, Zhenchao ZHU

“…The most problem in analysis of communication protocols and communication data for mobile terminals is that many mobile applications do not have the relevant public technical documents,and it is difficult to know the type of communication protocol it adopts.The instruction execution sequence analysis technique takes the instruction sequence executed by the program as a research object,and inversely infers the message format and the state machine to obtain the communication protocol.However,due to the incomplete collection of sequence information,the state machine infers that the inference is incomplete and cannot be effective.A novel protocol reverse scheme based on state machine comparison is proposed,which can be used for the forensics of mobile terminal communication data.The scheme first uses PIN for dynamical identification of the taint,and track it and analyzes the trajectory to obtain the message format.Secondly,the message clustering is performed on the basis of the message format to infer the protocol state machine.Finally,the LCS algorithm is used to compare the state machines to get a complete protocol state machine.This article tests and evaluates the scheme based on two types of application design experiments on the Android platform.The experimental results show that the results are both complete and real-time,and have practical value.…”
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AFD: Defending Convolutional Neural Networks Without Using Adversarial Samples by Nupur Thakur, Yuzhen Ding, Baoxin Li

“…The vulnerability of deep neural networks to adversarial attacks has attracted much research effort. Still, studies have shown that it is challenging to simultaneously achieve both strong robustness to adversarial attacks and low degradation in the performance on the original task, as there is always a trade-off between the two objectives. …”
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Accurate Solar Radiation Forecasting Through Feature-Enhanced Decision Trees and Wavelet Decomposition by Gaizen Soufiane, Abbou Ahmed, Fadi Ouafia

“…This study explores the efficacy of the decision tree algorithm in predicting solar power generation, addressing the inherent variability in photovoltaic (PV) energy production due to weather conditions. …”
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Disturbance Rejection and Uncertainty Analysis in Wind Turbines Using Model Predictive Control by Alok Kumar, Atul Kelkar

“…We have tailored the algorithm to the practical parameters of the National Renewable Energy Laboratory’s (NREL) Controls Advanced Research Turbine (CART) model. …”
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Crowd-based collaboration caching mechanism in smart identifier network by Haifeng LI, Wei QUAN, Nan CHENG, Hongke ZHANG, Xuemin SHEN

“…Smart identifier network (SINET) is an innovative network architecture.Through dynamic collaboration of service resource,function groups and physical components,the network scalability,resource utilization and service quality were effectively improved by SINET,and an effective solution for the development of industrial Internet of things(IoT) could be provided.To promote content delivery in resource-constrained IoT,caching function was introduced in network components by SINET,and the bandwidth waste caused by traffic redundancy in resource-constrained node could be reduced.Therefore,how to efficiently cache content became an important research topic.Based on SINET architecture,a crowd-based collaboration cache (C2Cache) mechanism was proposed in this scheme.According to the actual network topology,the caching function group was dynamically created and optimized by C2Cache,and a function group as crowd minimum unit to execute the maximum benefit cache (MBC) algorithm was defined to maximize the caching space efficiency.With the self-developed emulation system,named EmuStack,the performance of C2Cache was evaluated.The experimental results show that,comparing with LCE,Random,Prob Cache,LCD and Greedy caching mechanisms,the cache hit rate can be improved effectively,then the average access time can be reduced significantly by C2Cache.In the simulated network scenario,the performance increases 15% to 30%.…”
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Pearson Autocovariance Distinct Patterns and Attention-Based Deep Learning for Wind Power Prediction by W. G. Jency, J. E. Judith

“…Swift development in wind power and extension of wind generation necessitates significant research in numerous fields. Due to this, wind power is weather dependent; it is fluctuating and is sporadic over numerous time periods. …”
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Post-Quantum Homomorphic Encryption: A Case for Code-Based Alternatives by Siddhartha Siddhiprada Bhoi, Arathi Arakala, Amy Beth Corman, Asha Rao

“…Homomorphic Encryption (HE) allows secure and privacy-protected computation on encrypted data without the need to decrypt it. Since Shor’s algorithm rendered prime factorisation and discrete logarithm-based ciphers insecure with quantum computations, researchers have been working on building post-quantum homomorphic encryption (PQHE) algorithms. …”
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