Fuzzy Guiding of Roulette Selection in Evolutionary Algorithms by Krzysztof Pytel

“…This paper presents, discusses, and tests a novel method for guiding roulette selection in evolutionary algorithms. The new method uses fuzzy logic and incorporates information from both current and historical generations to predict the best scheme for the selection process. …”
Get full text

Quantum-annealing-inspired algorithms for multijet clustering by Hideki Okawa, Xian-Zhe Tao, Qing-Guo Zeng, Man-Hong Yung

“…We find that both the distance defined in the QUBO matrix and the prediction power of the QUBO solvers have crucial impacts on the multijet clustering performance. …”
Get full text

Prediction after a Horizon of Predictability: Nonpredictable Points and Partial Multistep Prediction for Chaotic Time Series by Vasilii A. Gromov, Philip S. Baranov

“…The resulting strategy demonstrates accurate results for both benchmark and real-world time series, with the number of predicted steps exceeding that of any other published algorithm.…”
Get full text

Post-extrasystolic variation of ST segment and T wave as a mortality risk predictor after myocardial infarction by Ralf J. Dirschinger, Ralf J. Dirschinger, Alexander Müller, Petra Barthel, Alexander Steger, Michael Dommasch, Axel Bauer, Karl-Ludwig Laugwitz, Georg Schmidt, Daniel Sinnecker, Daniel Sinnecker

Subjects: Get full text

ON DESIGN OF PREDICTIVE MODEL FOR HEART DISEASE by Soumyendu Bhattacharjee, Susmita Das, Sangita Roy, Arpita Santra, Anasuya Sarkar, Moumita Pa, Biswarup Neogi

“…We used several artificial intelligence (AI) techniques, such as the critical backslide and KNN, to predict and group patients with cardiovascular sickness. …”
Get full text

ALGORITHM OF TECHNOLOGICAL FORECASTING IN THE RUSSIAN FEDERATION by Victor Mikhaylovich Averbukh

Get full text

Association of weight-adjusted waist index and body mass index with chronic low back pain in American adults: a retrospective cohort study and predictive model development based on machine learning algorithms (NHANES 2009–2010) by Weiye Zhang, Weiye Zhang, Yan Li, Pengwei Shao, Yuxuan Du, Ke Zhao, Jiawen Zhan, Lee A. Tan

“…Six machine learning algorithms were employed to predict CLBP occurrence and identify the optimal algorithm.ResultsA total of 4,687 participants were included. …”
Get full text

Nonvariational ADAPT algorithm for quantum simulations by Ho Lun Tang, Yanzhu Chen, Prakriti Biswas, Alicia B. Magann, Christian Arenz, Sophia E. Economou

“…We compare this nonvariational algorithm with ADAPT-VQE and with feedback-based quantum algorithms in terms of the rate of energy reduction, the circuit depth, and the measurement cost in molecular simulation. …”
Get full text

FCC algorithm for power loss diminution by Kanagasabai L.

“…In this work, the FCC algorithm has been applied to the power problem. Real power loss reduction, voltage deviation minimization, and voltage stability enhancement are the key objectives of the proposed work. …”
Get full text

Investigation of Artificial Intelligence Techniques for the Management of Cataract Disease: A Systematic Review by Zahra Karbasi, Michaeel Motaghi Niko, Maryam Zahmatkeshan

“…Deep learning techniques, decision trees, and Bayesian algorithms were involved in cataract management. Machine learning algorithms such as logistic regression, random forest, artificial neural network, decision tree, K1-nearest neighbor, XGBoost, and adaptive boosting also played a role in cataract prediction. …”
Get full text

Advanced Classifiers and Feature Reduction for Accurate Insomnia Detection Using Multimodal Dataset by Ameya Chatur, Mostafa Haghi, Nagarajan Ganapathy, Nima TaheriNejad, Ralf Seepold, Natividad Martinez Madrid

“…Our findings emphasize the importance of tailoring feature sets and employing appropriate reduction techniques for optimal predictive modeling in sleep-related studies. …”
Get full text

Application of user preference mining algorithms based on data mining and social behavior in brand building by Yuhan Dong

“…In actual simulation experiments, its prediction results for the user’s brand preference index are accurate, with an error of only 0.11, and the algorithm has extremely high ratings among industry insiders. …”
Get full text

Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Saad Ahmed Dheyab, Shaymaa Mohammed Abdulameer, Salama Mostafa

“…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
Get full text

Performance Comparison of Data Reduction Techniques for Wireless Multimedia Sensor Network Applications by Pinar Sarisaray-Boluk, Kemal Akkaya

“…The results also indicate that data reduction techniques including BS algorithms and compression techniques can provide significant energy savings in terms of transmission energy costs.…”
Get full text

Construction of enhanced MRI-based radiomics models using machine learning algorithms for non-invasive prediction of IL7R expression in high-grade gliomas and its prognostic value in clinical practice by Jie Zhou

“…For selecting the most relevant features, we utilized the Minimum Redundancy Maximum Relevance (mRMR) and Recursive Feature Elimination (RFE) algorithms. Following this, we developed and assessed Support Vector Machine (SVM) and Logistic Regression (LR) models, measuring their performance through various metrics such as accuracy, specificity, sensitivity, positive predictive value, calibration curves, the Hosmer–Lemeshow goodness-of-fit test, decision curve analysis (DCA), and Kaplan–Meier survival analysis. …”
Get full text

Optimal Power Generation from Bagasse in a Sugarcane Plant using PSO Algorithm Compared to SQP Algorithm by Mohammad Askari Khanabadi, Imaneh Dehghani, Shahrokh Shojaeian

“…Due to the high amounts of sugarcane residue or bagasse which was produced by sugarcane plants in Iran, this study was aimed to optimize power generation from bagasse biomass in sugarcane plants using Particle Swarm Optimization (PSO) algorithm by data obtained from several case studies which had been simulated with SQP (Sequential quadratic programming) algorithm. …”
Get full text

Integration of multi agent reinforcement learning with golden jackal optimization for predicting average localization error in wireless sensor networks by K. Lakshmi Prabha, Hanan Abdullah Mengash, Hamed Alqahtani, Randa Allafi

Subjects: “…Multi agent reinforcement learning algorithm…”
Get full text

Comparative study on RF-BP model prediction of mining water-conducting fracture zone height in Binchang Coal Mine by Yadong JI, Xuan LIU, Kaipeng ZHU, Chunhu ZHAO, Kai LI, Chenhan YUAN, Panpan LI, Pengzhen YAN

“…Back propagation neural network, genetic algorithm and particle swarm optimization were used to optimize BP neural network and random forest algorithm to carry out regression fitting for the interpolated data. …”
Get full text

Model-based iterative reconstruction with adaptive regularization for artifact reduction in electron tomography by Singanallur Venkatakrishnan, Obaidullah Rahman, Lynda Amichi, Jose D. Arregui-Mena, Haoran Yu, David A. Cullen, Amirkoushyar Ziabari

“…In this paper, we present a two-stage algorithm based on metal artifact reduction, utilizing model-based iterative reconstruction methods with adaptive adjustment of regularization parameters. …”
Get full text

Analysis of software methods for metal computed tomography artifact reduction: experimental research by A. V. Petraikin, Yu. A. Vasilev, Z. R. Artyukova, A. K. Smorchkova, D. S. Semenov, А. А. Baulin, A. A. Alikhanov, R. A. Erizhokov, O. V. Omelyanskaya

“…It was also shown that O‑MAR forms additional artifacts near the HJE.Conclusion. Metal artifact reduction algorithms do not distort the X‑ray density without an artifact source. …”
Get full text