K-Gen PhishGuard: an Ensemble Approach for Phishing Detection with K-Means and Genetic Algorithm by Ali Al-Hafiz, Adnan Jabir, Shamala Subramaniam

“…In the first phase, the best set of features is identified by the Genetic algorithm and is utilised by the K-means clustering algorithm to divide the dataset into groups with similar traits. …”
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Infrared Aircraft Detection Algorithm Based on High-Resolution Feature-Enhanced Semantic Segmentation Network by Gang Liu, Jiangtao Xi, Chao Ma, Huixiang Chen

“…In order to achieve infrared aircraft detection under interference conditions, this paper proposes an infrared aircraft detection algorithm based on high-resolution feature-enhanced semantic segmentation network. …”
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XAI-BO: an architecture using Grad-CAM technique to evaluate Bayesian optimization algorithms on deep learning models by Luyl-Da Quach, Nguyen Quoc Khang, Nguyen Thai-Nghe, Chi-Ngon Nguyen

“…Additionally, the research utilizes Grad-CAM to clarify the positive impact of parameter reduction when using the BO algorithm. Through evaluations based on hyperparameter data, performance by each iteration, accuracy, and model explainability, the study demonstrates that the BO algorithm optimizes hyperparameters through selective processes. …”
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Infrared Small Target Detection Algorithm Based on Improved Dense Nested U-Net Network by Xinyue Du, Ke Cheng, Jin Zhang, Yuanyu Wang, Fan Yang, Wei Zhou, Yu Lin

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Inverse Design of Broadband Dispersion Compensation Fiber Based on Deep Learning and Differential Evolution Algorithm by Fuxiao Ma, Yunjie Ma, Peili Li, Weihua Shi

“…It is inversely designed by using artificial neural network (ANN) combined with differential evolution algorithm (DE) to obtain target dispersion compensation. …”
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Research on Universal Time/Length of Day Combination Algorithm Based on Effective Angular Momentum Dataset by Xishun Li, Yuanwei Wu, Dang Yao, Jia Liu, Kai Nan, Zewen Zhang, Weilong Wang, Xuchong Duan, Langming Ma, Haiyan Yang, Haihua Qiao, Xuhai Yang, Xiaohui Li, Shougang Zhang

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Effectiveness of physician-based diagnosis versus diagnostic artificial intelligence algorithms in detecting communicable febrile diseases in Mexico by Enrique Alonso Medina Fuentes, Carmen Alicia Ruíz Valdez, Porfirio Felipe Hernández Bautista, David Alejandro Cabrera Gaytán, Guadalupe Minerva Olivas Fabela, José Alberto Mireles Garza, Olga María Alejo Martínez, Brenda Leticia Rocha Reyes, Alfonso Vallejos Parás, Lumumba Arriaga Nieto, Yadira Pérez Andrade, Leticia Jaimes Betancourt, Gabriel Valle Alvarado, Oscar Cruz Orozco, Mónica Grisel Rivera Mahey

“…Methods An observational, descriptive, and retrospective study was conducted in a second-level hospital from 1 January 2022 to 31 December 2023, to determine Cohen's kappa and the sensitivity, specificity, positive and negative predictive values, precision and Youden's J index of diagnostic algorithms for 20 communicable diseases with respect to the doctors’ diagnoses. …”
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Optimized Dynamic Deployment of UAVs in Maritime Networks with Route Prediction by Yanli Xu, Yalan Shi

“…The prediction results are then used to guide the Proximal Policy Optimization (PPO) algorithm for the dynamic deployment of UAVs. …”
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Rolling Force Prediction of Hot Rolling Based on GA-MELM by Jingyi Liu, Xinxin Liu, Ba Tuan Le

“…In this paper, a rolling force prediction method based on genetic algorithm (GA), particle swarm optimization algorithm (PSO), and multiple hidden layer extreme learning machine (MELM) is proposed, namely, PSO-GA-MELM algorithm, which takes MELM as the basic model for rolling force prediction. …”
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Load prediction based elastic resource scheduling strategy in Flink by Ziyang LI, Jiong YU, Yuefei WANG, Chen BIAN, Yonglin PU, Yitian ZHANG, Yu LIU

“…In order to solve the problem that the load of big data stream computing platform fluctuates drastically while the cluster was suffering from the performance bottleneck due to the shortage of computing resources,the load prediction based elastic resource scheduling strategy in Flink (LPERS-Flink) was proposed.Firstly,the load prediction model was set up as the foundation to propose the load prediction algorithm and predict the variation tendency of the processing load.Secondly,the resource judgment model was set up to identify the performance bottleneck and resource redundancy of the cluster while the resource scheduling algorithm was proposed to draw up the resource rescheduling plan.Finally,the online load migration algorithm was proposed to execute the resource rescheduling plan and migrate processing load among nodes efficiently.The experimental results show that the strategy provides better performance promotion in the application with drastically fluctuating processing load.The scale and resource configuration of the cluster responded to the variation of processing load in time and the communication overhead of the load migration was reduced effectively.…”
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Protein homodimers structure prediction based on deep neural network by A. Y. Hadarovich, A. A. Kalinouski, A. V. Tuzikov

“…Recently Deep Neural Networks allowed to predict structures of individual proteins greatly prevailing in accuracy over other algorithmic approaches. …”
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Road Accident Prediction Model for the Roads of National Significance of Lithuania by Vilma Jasiūnienė, Donatas Čygas

“…Chapter 4 describes the testing and analysis of software intended for the implementation of accident prediction algorithm.…”
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Construction and evaluation of yeast expression networks by database-guided predictions by Katharina Papsdorf, Siyuan Sima, Gerhard Richter, Klaus Richter

“…We then show the ability of our networks to accurately predict further differentially expressed genes. Including these predicted genes into the networks improves the network quality and allows quantifying the predictive strength of the networks based on a newly implemented scoring method. …”
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Research on COP Prediction Model of Chiller Based on PSO-SVR by Zhou Xuan, Cai Panpan, Lian Sizhen, Yan Junwei

“…The results shows that the prediction accuracy of SVR model based on PSO optimization algorithm is higher than that of BP neural network and the relative error is within 3%. …”
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Prediction of the Electricity Demand in the Market: An Application of Optimization and Machine Learning by Ahmed Majed Althahabi, Hassan Mohammed Abed, Raed Khalid, Abrar Ryadh, Ali Al Mansor, Kadhum Al-Majdi, Adil Abbas Alwan

“…In this study, the combination of Gray Wolf Optimization and Artificial neural networks (GWO-ANN) algorithm was applied to predict the long-term electricity demand in Iraq, considering the nonlinear trend and uncertainties in the variables affecting it. …”
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Prediction of complex organic compounds activity with artificial neural networks. by E. V. Burljaeva, P. A. Ushakov

“…The analysis of neural networks applicability for complex organic compounds activity prediction is provided. The regulation algorithm is offered to improve the prediction properties of the networks.…”
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System load trend prediction method based on IF-EMD-LSTM by Jing Yu, Feng Ding, Chenghao Guo, Yabin Wang

“…Second, in order to further improve the prediction accuracy, the empirical modal decomposition algorithm is used to decompose the input data into intrinsic mode function (IMF) components of different frequencies. …”
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Prediction of Students’ Performance Based on the Hybrid IDA-SVR Model by Huan Xu

“…The aim of this study is to propose a novel intelligent approach to predict students’ performance using support vector regression (SVR) optimized by an improved duel algorithm (IDA). …”
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Prediction of Low-Temperature Rheological Properties of SBS Modified Asphalt by Qian Chen, Chaohui Wang, Liang Song

“…The extreme learning machine (ELM) algorithm optimized by genetic algorithm (GA) was used to quickly predict the low-temperature rheological properties of styrenic block copolymer (SBS) modified asphalt through the properties of the raw materials. …”
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Proposing a Novel Method for Optimal Location Finding Based on Machine Learning Algorithms and Gray Wolf Optimization by Fatemeh Heydari Pirbasti, Mahmoud Modiri, Kiamars Fathi-Hafshejani, Alireza Rashidi-Komijan

“…Proposed clustering method is evaluated and compared with some metaheuristics algorithm. The simulation results of the proposed method show cost reduction in finding the desired locations compared to similar researches. …”
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