Improving Cost Contingency Estimation in Infrastructure Projects with Artificial Neural Networks and a Complexity Index by Michael C. P. Sing, Qiuwen Ma, Qinhuan Gu

“…These findings not only advance the theoretical framework of ML algorithms for cost contingency prediction by implementing interval predictions but also provide practitioners with improved ML-based tools for more accurate infrastructure project cost performance predictions.…”
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Improvement of an Edge-IoT Architecture Driven by Artificial Intelligence for Smart-Health Chronic Disease Management by William Alberto Cruz Castañeda, Pedro Bertemes Filho

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Application of adaptive virtual synchronous generator based on improved active power loop in photovoltaic storage systems by Youzhuo Zheng, Yutao Xu, Yekui Yang, Long Hua, Yuqing Yang

“…Then, the adaptive inertia algorithm is incorporated into the active power loop of the VSG control, and an adaptive inertia control method based on the improved active power loop is proposed. …”
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A Metric Learning-Based Improved Oriented R-CNN for Wildfire Detection in Power Transmission Corridors by Xiaole Wang, Bo Wang, Peng Luo, Leixiong Wang, Yurou Wu

“…Compared with other commonly used object detection algorithms, the model developed in this study exhibited improved detection performance on the test dataset, offering research support for wildfire monitoring in power transmission corridors.…”
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StratLearn-z: Improved photo-$z$ estimation from spectroscopic data subject to selection effects by Chiara Moretti, Maximilian Autenrieth, Riccardo Serra, Roberto Trotta, David A. van Dyk, Andrei Mesinger

“…We benchmark our results against the GPz algorithm, quantifying the performance of the two algorithms with a set of metrics. …”
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Underwater image dehazing using a hybrid GAN with bottleneck attention and improved Retinex-based optimization by Amandeep Kaur, Shalli Rani, Mohammad Shabaz

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Improved estimation of two-phase capillary pressure with nuclear magnetic resonance measurements via machine learning by Oriyomi Raheem, Misael M. Morales, Wen Pan, Carlos Torres-Verdín

“…In contrast, nuclear magnetic resonance (NMR) measurements, which provide information on pore body size distribution, are faster and can be leveraged to estimate capillary pressure using machine learning algorithms. Recently, artificial intelligence methods have also been applied to capillary pressure prediction (Qi et al., 2024).Currently, no readily applicable predictive model exists for estimating an entire capillary pressure curve directly from standard petrophysical logs and core data. …”
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Anterior cruciate ligament tear detection based on Res2Net modified by improved Lévy flight distribution by Peiji Yang, Yanan Liu, Fei Liu, Mingxia Han, Yadegar Abdi

“…By optimizing the model using the ILFD algorithm, the diagnostic efficiency is greatly improved. …”
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Software-Based Transformation of White Light Endoscopy Images to Hyperspectral Images for Improved Gastrointestinal Disease Detection by Chien-Wei Huang, Chang-Chao Su, Chu-Kuang Chou, Arvind Mukundan, Riya Karmakar, Tsung-Hsien Chen, Pranav Shukla, Devansh Gupta, Hsiang-Chen Wang

“…<b>Conclusions:</b> These results confirm that the SAVE algorithm significantly improves the early identification and classification of GID, therefore providing a potential development towards more accurate, non-invasive GID diagnostics with WCE.…”
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Small Sample Fiber Full State Diagnosis Based on Fuzzy Clustering and Improved ResNet Network by Xiangqun Li, Jiawen Liang, Jinyu Zhu, Shengping Shi, Fangyu Ding, Jianpeng Sun, Bo Liu

“…In response to this issue, this paper proposes a communication fiber state diagnosis model based on fuzzy clustering and an improved ResNet. …”
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TTG-Text: A Graph-Based Text Representation Framework Enhanced by Typical Testors for Improved Classification by Carlos Sánchez-Antonio, José E. Valdez-Rodríguez, Hiram Calvo

“…Unlike traditional TF-IDF weighting, TTG-Text leverages typical testors to enhance feature relevance within text graphs, resulting in improved model interpretability and performance, particularly for smaller datasets. …”
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An Improved Velocity-Aided Method for Smartphone Single-Frequency Code Positioning in Real-World Driving Scenarios by Zhaowei Han, Xiaoming Wang, Jinglei Zhang, Shiji Xin, Qiuying Huang, Sizhe Shen

“…Additionally, using more refined observation models and appropriate parameter estimation algorithms led to a slight 6% improvement in velocity performance. …”
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Coverage path planning for multi-AUV considering ocean currents and sonar performance by Xukai Mu, Wei Gao

“…First, the necessary sampling points for the area coverage are identified based on the sonar detection range at different locations, which is calculated by combining the ocean acoustics model with the sonar equation. Second, an improved Dijkstra algorithm is presented to solve the adjacency matrix of the graph formed by all sampling points under the influence of ocean currents. …”
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Geological disaster risk assessment based on remote sensing, GIS, and a multi-strategy improved GWO-optimized Elman neural network by Kuayue Chen, Fuhong Bai, Ting Wang, Yingmei Su, Baoyun Wang

“…To improve the accuracy and intelligence of geological disaster risk assessment, this study proposes a novel method based on a Multi-strategy Improved Grey Wolf Optimization algorithm combined with the Elman Neural Network (MIGWO-Elman). …”
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A Hybrid Strategy Two‐Dimensional Concrete Aggregate Filling Algorithm by Xu Tian, Jun Ao, ChunBo Ma, JunJie Shi, HanJun Guo

“…Then, the algorithm's effectiveness in improving the modeling efficiency is verified by reconstruction experiments on random aggregate models with different aggregate grades. …”
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Asynchronous perception algorithm based on energy detection by Pan YU, Bin LI, Cheng-lin ZHAO

“…In the future heterogeneous wireless networks,since primary user (PU) and cognitive secondary user (SU) are not coordinated to be synchronous,it will result in sense timing difference between PU’s transmitter and SU’s receiver.For this asynchronous sense case,a new asynchronous sensing algorithm based on Bayesian estimation theory was proposed.A unified dynamic state space model was first proposed to describe the observable energy relationship with dynamic PU state and unknown timing difference.Then,an iterative estimation scheme was designed using stochastic finite set and the rules of maximum posterior probability.Finally,approximated estimation results were obtained by using a particle filter.The simulation results show that the proposed asynchronous scheme significantly eliminates the uncertainty of the received signal information and thus improves the spectrum sensing performance by obtaining the time difference accurately.…”
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Review on algorithms of dealing with depressions in grid DEM by Yi-Jie Wang, Cheng-Zhi Qin, A-Xing Zhu

“…Existing ways of improving the computation efficiency of depression-processing algorithms are also presented, i.e. serial algorithm optimization and parallel algorithms. …”
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Nowcasting of rainfall based on extrapolation and evolution algorithms. Preliminary results by Mateusz Giszterowicz, Katarzyna Ośródka, Jan Szturc

“…The paper gives an overview of algorithms used in the SNAR model and provides preliminary results.…”
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Coordinated Optimization Method for Distributed Energy Storage and Dynamic Reconfiguration to Enhance the Economy and Reliability of Distribution Network by Caihong Zhao, Qing Duan, Junda Lu, Haoqing Wang, Guanglin Sha, Jiaoxin Jia, Qi Zhou

“…Subsequently, a hybrid optimization algorithm combining an improved Aquila Optimizer-Second-Order Cone Programming (IAO-SOCP) is proposed to solve the coordinated optimization model. …”
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Integrating structured and unstructured data for livestock price forecasting: a sustainability study from South Korea by Yifan Zhu, Yifan Zhu, Yifan Zhu, Tserenpurev Chuluunsaikhan, Jong-Hyeok Choi, Aziz Nasridinov

“…Additionally, we develop a Korean-language sentiment lexicon using an improved Term Frequency–Inverse Document Frequency (ITF-IDF) algorithm, enabling morpheme-level sentiment analysis for better sentiment extraction in Korean contexts. …”
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