Demonstration of Algorithmic Quantum Speedup for an Abelian Hidden Subgroup Problem by Phattharaporn Singkanipa, Victor Kasatkin, Zeyuan Zhou, Gregory Quiroz, Daniel A. Lidar

“…For sufficiently small values of w and for circuits involving up to 58 qubits, we demonstrate an exponential speedup, albeit of a lower quality than the speedup predicted for the noiseless algorithm. The speedup exponent and the range of w values for which an exponential speedup exists are significantly enhanced when the computation is protected by dynamical decoupling. …”
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Resource Allocation Algorithm Based on Profit Maximization for Crowd Sensing by Kun Gao, Bin Wang, Xinwu Yu

“…The experimental results show that the new algorithm is feasible and superior to the traditional algorithms.…”
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Construction and Analysis of Macroeconomic Forecasting Model Based on Biclustering Algorithm by Chao Pang

“…The result of the biclustering algorithm has its unique advantages in mining the commonalities of various provinces under certain attribute sets.…”
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Analysis of Brand Visual Design Based on Collaborative Filtering Algorithm by Gao Chaomeng, Wang Yonggang

“…Finally, the collaborative filtering algorithm is optimized to improve the consumer similarity based on the original algorithm. …”
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Algorithm of Estimating Import-Substitution Based on Costs – Output Tables by N. A. Moiseev, B. A. Akhmadeev

“…The designed algorithm can be used as a support system for decision-making in importsubstitution policy.…”
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A Partition-Based Hybrid Algorithm for Effective Imbalanced Classification by Kittipong Theephoowiang, Anantaporn Hanskunatai

“…The algorithm identifies different data types, pairs them, and trains multiple models, which then vote on predictions using weighted strategies to ensure stable performance and minimize overfitting. …”
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Extended Blahut–Arimoto Algorithm for Semantic Rate-Distortion Function by Yuxin Han, Yang Liu, Yaping Sun, Kai Niu, Nan Ma, Shuguang Cui, Ping Zhang

“…Furthermore, by considering the semantic knowledge base (SKB) as a specific instance of synonymous mapping, the EBA algorithm provides a theoretical approach for analyzing and predicting the SKB size. …”
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Variational Autoencoders-Based Algorithm for Multi-Criteria Recommendation Systems by Salam Fraihat, Qusai Shambour, Mohammed Azmi Al-Betar, Sharif Naser Makhadmeh

“…The VAE-MCRS model utilizes the latent features generated by the VAE in conjunction with user–item interactions to enhance recommendation accuracy and predict ratings for unrated items. Experiments carried out using the Yahoo! …”
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Explainable AI based LightGBM prediction model to predict default borrower in social lending platform by Li-Hua Li, Alok Kumar Sharma, Sheng-Tzong Cheng

“…This paper proposes an explainable AI (XAI)-based prediction model utilizing the LightGBM algorithm to predict the likelihood of borrower default on a social lending platform. …”
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Reversible Data Hiding in Encrypted Images Based on Edge-Directed Prediction and Multi-MSB Self-Prediction by Yingqiang Qiu

“…A binary location map marks the prediction errors for each bit-plane. After being losslessly compressed using the Joint Bi-level Image Experts Group (JBIG) algorithm, the location maps are embedded into the encrypted image as auxiliary data, thereby creating ample room for embedding additional data. …”
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A Comparative Analysis of Machine Learning Algorithms for Classification of Diabetes Utilizing Confusion Matrix Analysis by Maad M. Mijwil, Mohammad Aljanabi

“…The study determined that three algorithms are very effective at prediction. Mainly, logistic regression and Adaboost had a classification rate above 92%, and the naive bayes algorithm achieved a classification rate above 90%. …”
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AI-based algorithms for estimating hydrochar properties in terms of biomass ultimate analysis by Raouf Hassan, Ali sharifzadegan, Alireza Baghban

“…The CatBoost model outperformed other algorithms for HHV prediction, yielding an R² of 0.9788, an MSE of 1.63, and an MRD of 3.71 %. …”
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Assessment of Information predictability of stochastic processes by A. V. Ausiannikau

“…The necessary theoretical information for parameter estimation algorithms informational predictability of stochastic processes. …”
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Predicting dementia in people with Parkinson’s disease by Mohamed Aborageh, Tom Hähnel, Patricia Martins Conde, Jochen Klucken, Holger Fröhlich

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A “Salt and Pepper” Noise Reduction Scheme for Digital Images Based on Support Vector Machines Classification and Regression by Hilario Gómez-Moreno, Pedro Gil-Jiménez, Sergio Lafuente-Arroyo, Roberto López-Sastre, Saturnino Maldonado-Bascón

“…A modified median filter based on a previous noise detection stage and a regression-based filter are presented and compared to other well-known state-of-the-art noise reduction algorithms. The results show that the filters proposed achieved good results, outperforming other state-of-the-art algorithms for low and medium noise ratios, and were comparable for very highly corrupted images.…”
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Review of pedestrian trajectory prediction methods by Linhui LI, Bin ZHOU, Weiwei REN, Jing LIAN

“…With the breakthrough of deep learning technology and the proposal of large data sets, the accuracy of pedestrian trajectory prediction has become one of the research hotspots in the field of artificial intelligence.The technical classification and research status of pedestrian trajectory prediction were mainly reviewed.According to the different modeling methods, the existing methods were divided into shallow learning and deep learning based trajectory prediction algorithms, the advantages and disadvantages of representative algorithms in each type of method were analyzed and introduced.Then, the current mainstream public data sets were summarized, and the performance of mainstream trajectory prediction methods based on the data sets was compared.Finally, the challenges faced by the trajectory prediction technology and the development direction of future work were prospected.…”
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Algorithms Facilitating the Observation of Urban Residential Vacancy Rates: Technologies, Challenges and Breakthroughs by Binglin Liu, Weijia Zeng, Weijiang Liu, Yi Peng, Nini Yao

“…The ensemble learning algorithm combines multiple prediction models to improve the prediction accuracy and stability. …”
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Efficient Pathfinding on Grid Maps: Comparative Analysis of Classical Algorithms and Incremental Line Search by Amr Elshahed, Majid Khan Bin Majahar Ali, Ahmad Sufril Azlan Mohamed, Farah Aini Binti Abdullah, Ts. Lee Jian Aun

“…On average, ILS achieved a 87.31% reduction in execution time and a 71.44% reduction in node expansions compared to their standard counterparts. …”
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Performance Comparison of Random Forest and Decision Tree Algorithms for Anomaly Detection in Networks by Rafiq Fajar Ramadhan, Wahid Miftahul Ashari

“…However, in multi-class data, Random Forest showed slightly better performance, though it required significantly more time for training and prediction. Despite the small difference in accuracy, Decision Tree demonstrated faster prediction times, making it more efficient for time-sensitive applications. …”
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Adaptive Model Predictive Control for 4WD-4WS Mobile Robot: A Multivariate Gaussian Mixture Model-Ant Colony Optimization for Robust Trajectory Tracking and Obstacle Avoidance by Hayat Ait Dahmad, Hassan Ayad, Alfonso García Cerezo, Hajar Mousannif

“…This study uses a nonlinear model predictive controller (MPC) to ensure accurate trajectory tracking of a four-wheel drive, four-wheel steer (4WD-4WS) mobile robot. …”
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