Automating Colon Polyp Classification in Digital Pathology by Evaluation of a “Machine Learning as a Service” AI Model: Algorithm Development and Validation Study by David Beyer, Evan Delancey, Logan McLeod

“… BackgroundArtificial intelligence (AI) models are increasingly being developed to improve the efficiency of pathological diagnoses. …”
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Optimization Design of Multi-Blade Centrifugal Fan Based on Variable Weight PSO-BP Prediction Model and Multi-Objective Beluga Optimization Algorithm by Wenyang Jin, Jiaxuan Wang, Junyu Li, Ren Xu, Ming Zhou, Qibai Huang

“…This article proposes a prediction model and a multi-objective optimization algorithm and applies them to the optimization design of a multi-blade centrifugal fan. …”
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A Dendritic Neural Network-Based Model for Residential Electricity Consumption Prediction by Ting Jin, Rui Xu, Kunqi Su, Jinrui Gao

“…In this study, a dendritic neural network-based model (DNM), combined with the AdaMax optimization algorithm, is used to predict residential electricity consumption. …”
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Designing a new tomato leaf disease classification framework using ran-based adaptive fuzzy c-means with heuristic algorithm model by Kanti Rongali Divya, Rao Gottapu Sasibhushana, Aruna Singam

“…So, the parameters of AFCM are tuned by utilizing the new improved algorithm named Dingo Optimization Algorithm (DOA) to improve the clustering accuracy. …”
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New Channel Estimation Algorithm for Non-Sample-Spaced Channels in Fast Time-Varying OFDM System by 刘顺兰, 汪佳丽

“…The simulation results show that the bit error rate and channel mean square error of the proposed algorithm are both effectively improved.…”
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New Channel Estimation Algorithm for Non-Sample-Spaced Channels in Fast Time-Varying OFDM System by 刘顺兰, 汪佳丽

“…The simulation results show that the bit error rate and channel mean square error of the proposed algorithm are both effectively improved.…”
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Multi-Innovation Stochastic Gradient Identification Algorithm for Hammerstein Controlled Autoregressive Autoregressive Systems Based on the Key Term Separation Principle and on the... by Huiyi Hu, Xiao Yongsong, Rui Ding

“…An input nonlinear system is decomposed into two subsystems, one including the parameters of the system model and the other including the parameters of the noise model, and a multi-innovation stochastic gradient algorithm is presented for Hammerstein controlled autoregressive autoregressive (H-CARAR) systems based on the key term separation principle and on the model decomposition, in order to improve the convergence speed of the stochastic gradient algorithm. …”
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Using Cuckoo Search Algorithm to Predict Corporate Financial Risks and Alleviate Economic Uncertainty by Muqiao Cai

“…CSA is used to tune the network weights and feature parameters worldwide to improve the neural model’s convergence speed and predictive ability. …”
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An Enhanced IDBO-CNN-BiLSTM Model for Sentiment Analysis of Natural Disaster Tweets by Guangyu Mu, Jiaxue Li, Xiurong Li, Chuanzhi Chen, Xiaoqing Ju, Jiaxiu Dai

“…The improved DBO (IDBO) algorithm is then utilized to optimize the Convolutional Neural Network—Bidirectional Long Short-Term Memory (CNN-BiLSTM) model’s hyperparameters. …”
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Research on Oil Well Production Prediction Based on GRU-KAN Model Optimized by PSO by Bo Qiu, Jian Zhang, Yun Yang, Guangyuan Qin, Zhongyi Zhou, Cunrui Ying

“…First, the MissForest algorithm is employed to handle anomalous data, improving data quality. …”
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Applicability of elite samples in solving the traveling salesman problem by Goldberg model by Valery G. Kobak, Irma S. Rudova

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Driving Supply Chain Transformation with IoT and AI Integration: A Dual Approach Using Bibliometric Analysis and Topic Modeling by Jerifa Zaman, Atefeh Shoomal, Mohammad Jahanbakht, Dervis Ozay

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Advanced long-term actual evapotranspiration estimation in humid climates for 1958–2021 based on machine learning models enhanced by the RReliefF algorithm by Ahmed Elbeltagi, Salim Heddam, Okan Mert Katipoğlu, Abdullah A. Alsumaiei, Mustafa Al-Mukhtar

“…This model is best suited for further research on AET prediction at the stations under investigation, which could improve irrigation and boost agricultural productivity.…”
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General statement of the challenge of selection of decisions to improve the protection of objects of life support from the population from the impact of air shock wave by Voskoboev V.F., Rybakov A.V., Ivanov E.V.

“…An algorithm for solving the problem is presented. A multi-factor model for assessing the security of an object against the impact of a shock wave is the basis of the algorithm. …”
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An Intelligent Fault Diagnosis Model for Rolling Bearings Based on IGTO-Optimized VMD and LSTM Networks by Xianglong Luo, Fengrong Yu, Jing Qian, Biao An, Nengpeng Duan

“…To address the issue of rolling bearing fault diagnosis, this paper proposes a novel model combining the Improved Gorilla Troop Optimization (IGTO) algorithm, Variational Mode Decomposition (VMD), Permutation Entropy (PE), and Long Short-Term Memory (LSTM) networks. …”
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Two stage malware detection model in internet of vehicles (IoV) using deep learning-based explainable artificial intelligence with optimization algorithms by Manal Abdullah Alohali, Sultan Alahmari, Mohammed Aljebreen, Mashael M. Asiri, Achraf Ben Miled, Sami Saad Albouq, Othman Alrusaini, Ali Alqazzaz

“…Besides, the proposed MDMIoV-DLXAI model utilizes the reptile search algorithm (RSA) model for feature selection. …”
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Construction of Clinical Predictive Models for Heart Failure Detection Using Six Different Machine Learning Algorithms: Identification of Key Clinical Prognostic Features by Qu FZ, Ding J, An XF, Peng R, He N, Liu S, Jiang X

“…Following the elimination of features with significant missing values, the remaining features were utilized to construct predictive models employing six machine learning algorithms. …”
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Driveway Detection for Weed Management in Cassava Plantation Fields in Thailand Using Ground Imagery Datasets and Deep Learning Models by Ithiphat Opasatian, Tofael Ahamed

“…In this context, deep learning algorithms have the potential to train models to detect driveways through furrow image segmentation. …”
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A Deep Learning Model for Identifying the Risk of Mesenteric Malperfusion in Acute Aortic Dissection Using Initial Diagnostic Data: Algorithm Development and Validation by Zhechuan Jin, Jiale Dong, Chengxiang Li, Yi Jiang, Jian Yang, Lei Xu, Ping Li, Zhun Xie, Yulin Li, Dongjin Wang, Zhili Ji

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Heuristic XAI: AIME and HMM Integration Improved-Feature-Importance Assessment Through Heuristics by Takafumi Nakanishi, Ponlawat Chophuk, Krisana Chinnasarn

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