Regeneration Filter: Enhancing Mosaic Algorithm for Near Salt & Pepper Noise Reduction by Ratko M. Ivković, Ivana M. Milošević, Zoran N. Milivojević

Get full text

Unsustainable artificial intelligence and algorithmically facilitated emissions: The case for emissions-reduction-by-design by Jutta Haider, Malte Rödl, James White

“…It introduces the notion of algorithmically facilitated emissions to initiate a shift from a logic of ‘climate collapse by design’ to a logic of ‘emissions reduction by design’. …”
Get full text

Improved HLLL Lattice Basis Reduction Algorithm to Solve GNSS Integer Ambiguity by Kezhao Li, Chendong Tian, Yingxiang Jiao, Zhe Yue

“…Compared with the LLL reduction algorithm and HLLL reduction algorithm, the experimental results show that the PHLLL algorithm has higher reduction efficiency and effectiveness. …”
Get full text

Optimization Algorithm of Workflow’s Accuracy Based  on Serial Reduction under Constraint Time by LUO Zhi-yong, ZHU Zi-hao, YOU Bo, MIAO Shi-di

“…Finally，in the typical case，the traditional one-way target algorithm and the string reduction algorithm are used to solve the corresponding path respectively， and analyzed the other parameters that affect the performance of SＲA. …”
Get full text

Neighborhood conditional mutual information entropy attribute reduction algorithm for hybrid data by Haibo LAN

“…Attribute reduction is an important research content of the rough set theory.Its main purpose is to eliminate irrelevant attributes in information systems, reduce data dimensions and improve data knowledge discovery performance.However, most of the attribute reduction methods based on a rough set do not consider the dependence between attributes, which makes the final attribute reduction result have some redundant attributes.An attribute reduction algorithm based on neighborhood conditional mutual information entropy was proposed.Firstly, based on the traditional neighborhood entropy, a hybrid neighborhood mutual information entropy model and a hybrid neighborhood conditional mutual information entropy model were proposed for hybrid data.Then, the two entropy models were used to evaluate the attribute dependence and attribute heuristic search of the hybrid information system, and an attribute reduction algorithm was designed.Finally, through the experimental analysis of UCI data sets, it was proved that the algorithm had higher attribute reduction performance.…”
Get full text

Improved Crosstalk Reduction on Multiview 3D Display by Using BILS Algorithm by Xiaoyan Wang, Chunping Hou

“…In this paper, we present a system-introduced crosstalk measurement method and derive an improved crosstalk reduction method. The proposed measurement method is applied to measure the exact crosstalk among subpixels corresponding to different view images and the obtained results are very effective for crosstalk reduction method. …”
Get full text

Incremental attribute reduction algorithm for dominance-based neighborhood relative decision entropy by CHEN Baoguo, CHEN Lei, DENG Ming, LI Xiaoyan, CHEN Jinlin

“…Verify the effectiveness of the incremental algorithm through these experimental results.ConclusionsThe experimental results show that the proposed incremental algorithm has better attribute reduction performance on dynamic datasets, significantly improving the efficiency of dynamic attribute reduction while ensuring the number of attribute selections and classification accuracy. …”
Get full text

Blind signal separation algorithm based on temporal predictability and differential search algorithm by Lei CHEN, Li-yi ZHANG, Yan-ju GUO, Yong HUANG, Jing-yi LIANG

Subjects: Get full text

Energy Optimization in Ultrasound Tomography Through Sensor Reduction Supported by Machine Learning Algorithms by Bartłomiej Baran, Tomasz Rymarczyk, Dariusz Majerek, Piotr Szyszka, Dariusz Wójcik, Tomasz Cieplak, Marcin Gąsior, Marcin Marczuk, Edmund Wąsik, Konrad Gauda

Get full text

Active noise reduction system by Wojciech CIESIELKA

Subjects: Get full text

Real power loss reduction by Rock Dove optimization and Fuligo Septica optimization algorithms by Kanagasabai L.

“…This paper aims to use the Rock Dove (RD) optimization algorithm and the Fuligo Septica optimization (FSO) algorithm for power loss reduction. …”
Get full text

Prediction of Hypertension Patients with Machine Learning Algorithm by Eko Priyono

“…These algorithms can predict hypertension risk based on clinical data, such as age, medical history, and lifestyle. …”
Get full text

Location prediction algorithm based on movement tendency by Wen LI, Shi-xiong XIA, Feng LIU, Lei ZHANG, Guan YUAN

“…A location prediction algorithm based on movement tendency (LP-MT) was proposed, which not only buils moving object's historical activity model borrowing from Markov thinking, but also added movement tendency as an important reference of location prediction. …”
Get full text

Neural network-based link prediction algorithm by Yonghao PAN, Hongtao YU, Shuxin LIU

Subjects: Get full text

Traffic Optimization Through Waiting Prediction and Evolutive Algorithms by Francisco García, Helena Hernández, María N. Moreno-García, Juan F. de Paz Santana, Vivian F. López, Javier Bajo

Subjects: “…evolutionary algorithm…”
Get full text

A Review of Link Prediction Algorithms in Dynamic Networks by Mengdi Sun, Minghu Tang

“…Furthermore, dynamic network link prediction algorithms are classified into regular sampling and irregular sampling by the method of network sampling. …”
Get full text

Comparative analysis of boosting algorithms for predicting personal default by Nhat Nguyen, Duy Ngo

Subjects: “…Personal default prediction…”
Get full text

Using machine learning algorithms to predict colorectal polyps by Xingjian Xiao, Shiyou Liu, Kubra Maqsood, Xiaohan Yi, Guoqun Xie, Hailei Zhao, Bo Sun, Jianying Mao, Xianglong Xu

“…Interpretation: Using non-invasive factors and machine learning algorithms can accurately predict the occurrence of colorectal polyps in individuals with positive initial screening results. …”
Get full text

Improving Prediction Algorithms for Cardiometabolic Risk in Children and Adolescents by Ulla Sovio, Aine Skow, Catherine Falconer, Min Hae Park, Russell M. Viner, Sanjay Kinra

“…We discuss the use of MetS scores and algorithms in an attempt to predict later cardiometabolic risk in children and adolescents and offer suggestions for developing clinically useful algorithms in this population. …”
Get full text

Student Performance Prediction Using Machine Learning Algorithms by Esmael Ahmed

“…The study found that the SVM algorithm had the best prediction results after parameter adjustment, with a 96% accuracy rate. …”
Get full text