Comparison of noise reduction algorithms. by Tianke Fang (22648035)

The reconstruction error and classification accuracy of the five algorithms on the six face databases. by Jing Wang (6206297)

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Folder with all data and algorithms by Jorge Servert Lerdo de Tejada (22290001)

Model-Based Clustering of Categorical Data Based on the Hamming Distance by Raffaele Argiento (647076)

“…The elements of this family are then considered as kernels of a finite mixture model with an unknown number of components. …”

Investigation on the accuracy and convergence speed of different swarm optimization algorithms. by Zixi Wang (459102)

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Mitochondrial toxic prediction of marine alga toxins using a predictive model based on feature coupling and ensemble learning algorithms by Guangyin Jia (21075537)

“…By comparing 8 machine learning algorithms and using a weighted soft voting method to integrate the two optimal algorithms, we established 108 prediction models and identified the best ensemble learning model MACCS_LK for screening and defining its application domain. …”

File includes code "Transfer learning.R" and "updatebeta.cpp" for implementing transfer learning methods. by Lulu Pan (8977979)

Flowchart of hybrid genetic algorithm combining simulated annealing and greedy methods. by Zixi Wang (459102)

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Computational Domain: The computational domain was discretized using conformal tetrahedral elements, resulting in a total of 926K elements. by Martina Bukač (20161460)

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”

Spatial spectrum of the 100th frame under array distortion conditions (20 elements). by Gaoxiang Xing (21755689)

Schematic diagram of the end iterations of the genetic solution after the calculation of the greedy algorithm. by Zixi Wang (459102)

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Schematic diagram of the end iteration of the genetic solution after the calculation of the greedy algorithm. by Zixi Wang (459102)

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Comparison of PSNR values of different algorithms. by Xiaojun Wang (50332)

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Changes in FID values of different algorithms. by Xiaojun Wang (50332)

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Comparison of SSIM values of different algorithms. by Xiaojun Wang (50332)

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Changes in loss values for different algorithms. by Xiaojun Wang (50332)

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Overview of the C&CG method. by Tianhe Sun (21145341)

“…The model is solved iteratively using the column generation algorithm and strong duality theory. Case studies on a Northeast China power grid demonstrate that, by optimally configuring generation and storage capacity guided by flexibility and other indicators, the proposed method reduces curtailment/load shedding costs and system flexibility insufficiency probability by 45% and 4.3% respectively. …”

Power quality control algorithms for small scale power intergration systems by Advocate Mlamla (20170815)

“…The CPDs depend on the DC link voltage from the storage element used which is not always sufficient and the compensation of the power quality issues fail. …”

Source code for data mining from Apache JIRA project. by Susmita Haldar (17707125)