Evaluation of Automated Object-Detection Algorithms for Koala Detection in Infrared Aerial Imagery by Laith A. H. Al-Shimaysawee, Anthony Finn, Delene Weber, Morgan F. Schebella, Russell S. A. Brinkworth

“…In addition, fatigue and tedium associated with the difficult and repetitive task of checking every tree means automated detection options are particularly desirable. …”
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Using Features Extracted From Upper Limb Reaching Tasks to Detect Parkinson’s Disease by Means of Machine Learning Models by Giuseppe Cesarelli, Leandro Donisi, Francesco Amato, Maria Romano, Mario Cesarelli, Giovanni D'Addio, Alfonso M. Ponsiglione, Carlo Ricciardi

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Trend equation prediction in medical and pharmaceutical studies (the example of respiratory diseases development in children in the region) by O. V. Zhukova, S. V. Kononova, T. M. Konyshkina

“…Prediction analysis was based on the trend lines, which displayed the functions from the mean values of the analyzed indicators. The function selection was determined by the temporal data changes. …”
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Improving long short-term memory (LSTM) networks for arbitrage spread forecasting: integrating cuckoo and zebra algorithms in chaotic mapping space for enhanced accuracy by Mingfu Zhu, Yaxing Liu, Panke Qin, Yongjie Ding, Zhongqi Cai, Zhenlun Gao, Bo Ye, Haoran Qi, Shenjie Cheng, Zeliang Zeng

“…Experimental results showed a mean absolute percentage error (MAPE) of 0.011, mean square error (MSE) of 3.326, mean absolute error (MAE) of 1.267, and coefficient of determination (R2) of 0.996. …”
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The impact of intravenous iodinated contrast agents on radiotherapy dose calculation and radiobiological effect predictions in central lung cancer by Defu Yang, Feng Shang, Ying Xu, Ying Yan

“…BackgroundAccurate dose calculation algorithms are critical for optimizing radiotherapy outcomes. …”
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Spatial Distribution of Poverty Clusters and Its Prediction Algorithms: A Visual Analytics Approach to Understanding the Disparities of Poverty Across Zones by Ngong'ho Bujiku Sende, Snehanshu Saha, Leon Fidele Ruganzu Uwimbabazi

“…Multidimensional poor and non-poor households were classified using the K-Means clustering algorithm, which demonstrated the highest performance among the nine clustering algorithms tested, effectively categorizing households into two clusters. …”
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Pediatric sepsis phenotypes for enhanced therapeutics: An application of clustering to electronic health records by Ioannis Koutroulis, Tom Velez, Tony Wang, Seife Yohannes, Jessica E. Galarraga, Joseph A. Morales, Robert J. Freishtat, James M. Chamberlain

“…Using feature sets used in related clustering studies, LCA and K‐means algorithms were used to derive 4 distinct phenotypic pediatric sepsis segmentations. …”
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Change Detection in Multitemporal High Spatial Resolution Remote-Sensing Images Based on Saliency Detection and Spatial Intuitionistic Fuzzy C-Means Clustering by Liang Huang, Qiuzhi Peng, Xueqin Yu

“…In order to improve the change detection accuracy of multitemporal high spatial resolution remote-sensing (HSRRS) images, a change detection method of multitemporal remote-sensing images based on saliency detection and spatial intuitionistic fuzzy C-means (SIFCM) clustering is proposed. Firstly, the cluster-based saliency cue method is used to obtain the saliency maps of two temporal remote-sensing images; then, the saliency difference is obtained by subtracting the saliency maps of two temporal remote-sensing images; finally, the SIFCM clustering algorithm is used to classify the saliency difference image to obtain the change regions and unchange regions. …”
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An effective parameter estimation on thermoelectric devices for power generation based on multiverse optimization algorithm by Luis Fernando Grisales-Noreña, Vanessa Botero-Gómez, Rubén Iván Bolaños, Faustino Moreno-Gamboa, Daniel Sanin-Villa

“…This evaluation considered various metrics, including the best solution of each algorithm, the mean solution, the standard deviation, and the time consumed on average on each run.…”
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Optimizing Solid Oxide Fuel Cell Performance Using Advanced Meta-Heuristic Algorithms by Siva Ram Rajeyyagari, Srinivas Nowduri

“…The models are evaluated against a comprehensive set of performance metrics: Root Mean Square Error (RMSE), Mean Squared Error (MSE), coefficient of determination (R²), correlation coefficient (R), Mean Absolute Error (MAE), Relative Absolute Error (RAE), Squared Error (SE), Mean Absolute Percentage Error (MAPE), and Normalized Mean Squared Error (NMSE). …”
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Multicenter Evaluation of Machine-Learning Continuous Pulse Rate Algorithm on Wrist-Worn Device by Weixuan Chen, Rafael Cordero, Jessie Lever Taylor, Domenico R. Pangallo, Rosalind W. Picard, Marisa Cruz, Giulia Regalia

“…Bias, mean absolute error (MAE), mean absolute percentage error (MAPE), limits of agreement (LoA), and Pearson and Lin’s concordance correlation coefficients (⍴ and CCC) were also computed. …”
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The Moving Average Algorithm for Forecasting Palm Oil Fresh Fruit Bunch (FFB) Prices by Zaid Ubay Siregar, Heri Santoso

“…The accuracy of the forecast is evaluated using several metrics: first, the Root Mean Squared Error (RMSE) with a value of 137.19, indicating moderate forecasting error; second, the Mean Absolute Percentage Error (MAPE) with a value of 6.09%, indicating good accuracy; and third, the Mean Absolute Error (MAE) with a value of 117.0, indicating relatively small errors. …”
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Assessing the Validity of Computerized Algorithms for Determining Pulse Wave Velocity: A Clinical Study by Amira Tairi, Hasan Obeid, Saliha Addour, Mark Butlin, Alberto P. Avolio, Catherine Fortier, Mohsen Agharazii

“…The PWVComp-2nd and PWVSphyg-IT were 9.48 ± 3.25 m/s and 9.59 ± 3.25 m/s with a mean difference of 0.11 ± 0.66 m/s (p = 0.04). Conclusion: The present study shows that the difference between the two algorithms is negligible across a wide range of PTT and hence does not support the need for adjusting PWV according to the algorithm used for determining PTT. …”
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Optimizing Renewable Energy Systems Placement Through Advanced Deep Learning and Evolutionary Algorithms by Konstantinos Stergiou, Theodoros Karakasidis

“…Validation against real-world data demonstrates improved prediction accuracy using metrics like root mean squared error (RMSE), mean absolute error (MAE), and mean absolute percentage error (MAPE). …”
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On Holt Winters Algorithm with Decomposition for Forecasting Financial Time Series with Complex Seasonal Patterns by منى نزيه على عبد البارى

“…The results of the study concluded that the Holt Winters Algorithm or triple exponential smoothing model is the best model since it produces the lowest Mean Absolute Percentage error (MAPE), Mean Absolute Deviation (MAD), and Mean Squared Deviation (MSD) values which are 4,380, 244783 compared to 4, 385, 246837 for SES, and 5, 410, 270734 for DES, and thus can be used to predict the monthly stock returns of the Saudi Stock Index.…”
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Multi-Objective Portfolio Optimization: An Application of the Non-Dominated Sorting Genetic Algorithm III by John Weirstrass Muteba Mwamba, Leon Mishindo Mbucici, Jules Clement Mba

“…This study evaluates the effectiveness of the Non-dominated Sorting Genetic Algorithm III (NSGA-III) in comparison to the traditional Mean–Variance optimization method for financial portfolio management. …”
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Construction and Demolition Waste Generation Prediction by Using Artificial Neural Networks and Metaheuristic Algorithms by Ruba Awad, Cenk Budayan, Asli Pelin Gurgun

“…Different performance parameters, such as mean absolute error (MAE), mean square error (MSE), root mean squared error (RMSE), and the coefficient of determination (R²), are used to evaluate the effectiveness of the models developed. …”
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Prediction of contact resistance of electrical contact wear using different machine learning algorithms by Zhen-bing Cai, Chun-lin Li, Lei You, Xu-dong Chen, Li-ping He, Zhong-qing Cao, Zhi-nan Zhang

“…To reduce testing time and costs and quickly obtain the electrical contact performance of H62 brass alloy after wear caused by different factors, three algorithms (random forest (RF), support vector regression (SVR), and BP neural network (BPNN)) were used to train and test experimental results, resulting in a machine learning model suitable for predicting the stable mean resistance of H62 brass alloy after wear. …”
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Video Refereeing Model of Soccer Match Based on Fuzzy Clustering and Cuckoo Optimization Algorithm by Ting Wang, Jinglong Geng, Jing Wang, Xiao Yan

“…The enhanced algorithm model, enhanced cuckoo-fuzzy C-mean algorithm model, cuckoo-fuzzy C-mean algorithm model, and fuzzy C-mean algorithm model had delineation effects of 0.80, 0.72, 0.70, and 0.61, in that order. …”
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Performance Analysis of Conventional Beamforming Algorithm for Angle-of-Arrival Estimation under Measurement Uncertainty by Eun-Kyung Lee, Joon-Ho Lee

“…The performance of the conventional beamforming for angle-of-arrival (AOA) estimation algorithm under measurement uncertainty is analyzed. …”
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