Studi Komparasi Naive Bayes, K-Nearest Neighbor, dan Random Forest untuk Prediksi Calon Mahasiswa yang Diterima atau Mundur by Puteri Sejati, Munawar Munawar, Marzuki Pilliang, Habibullah Akbar

“…This study used the classification method to predict prospective students. They are accepted or withdrawn. …”
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Hybrid active-passive thermal management system for deep wells: Long-term stability and multi-objective optimization by Zongwei Yao, Haomin Li, Hongxu Xu, Hongfei Yang, Qiushi Bi, Tianshuang Xu

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Multi-objective RGB-D fusion network for non-destructive strawberry trait assessment by Zhenzhen Cheng, Yifan Cheng, Bailing Miao, Tingting Fang, Shoufu Gong

“…This study proposes a multi-objective learning algorithm that leverages RGB-D multimodal information to estimate these quality metrics. …”
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Operation optimisation of direct current microgrids toward stability and economy: a model-data co-driven framework by Yuxin Zhu, Fei Wang, Zhengyu Lin, James Fleming

“…Case study illustrates that the proposed method is not affected by prediction errors and avoids the violation of stability constraints. …”
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Emerging opportunities and challenges for the future of reservoir computing by Min Yan, Can Huang, Peter Bienstman, Peter Tino, Wei Lin, Jie Sun

“…Shown to have the potential of achieving higher-precision prediction in chaotic systems, those pioneering works led to a great amount of interest and follow-ups in the community of nonlinear dynamics and complex systems. …”
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NEW APPROACHES IN TREATMENT OF PATIENTS WITH PERFORATED DUODENAL ULCER by P. N. Romashchenko, N. A. Maistrenko, A. E. Korovin, S. A. Sibirev, P. A. Sidorchuk

“…The results of conducted clinical study showed that in order to establish the correct preoperative diagnosis and the choice of rational treatment of patients with perforated duodenal ulcer it is necessary to conduct a purposeful complex investigation, including an assessment of general somatic state and the operative-anaesthetic risk of patients and changes of pyloroduodenal zone and the severity of peritonitis and prediction of lethality. The diagnostic algorithm let the authors make a diagnosis of perforated duodenal ulcer before the operation and decide on an adequate volume of surgical intervention. …”
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Efficient text-to-video retrieval via multi-modal multi-tagger derived pre-screening by Yingjia Xu, Mengxia Wu, Zixin Guo, Min Cao, Mang Ye, Jorma Laaksonen

“…We predict discrete semantic tags for video and text with our proposed multi-modal multi-tagger module, and then leverage an inverted index for space-efficient and fast tag matching to filter out irrelevant videos. …”
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Enhancing Security of Databases through Anomaly Detection in Structured Workloads by Charanjeet Dadiyala, Faijan Qureshi, Kritika Anil Bhattad, Sourabh Thakur, Nida Tabassum Sharif Sheikh, Kushagra Anil Kumar Singh

“…Structured workloads typically exhibit predictable patterns of data access and usage, making them susceptible to displaying anomalies that may indicate unauthorized access, data manipulation, or other security breaches. …”
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Three-Dimensional Path Planning of AUVs in Dynamic Obstacle Environments by Chaoyang CHEN, Yute TANG, Yi HUANG, Zhiqun LIU

“…Moreover, dynamic obstacle trajectories were modeled, and the Singer model, combined with the Kalman filter algorithm, was used to precisely predict obstacle states, thereby enhancing the dynamic obstacle avoidance capabilities of AUVs. …”
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Fuzzy-Logic-Based Energy Optimized Routing for Wireless Sensor Networks by Haifeng Jiang, Yanjing Sun, Renke Sun, Hongli Xu

“…We adopt the social welfare function to predict inequality of residual energy of neighbors after selecting different next hop nodes. …”
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A Novel Method for ECG-Free Heart Sound Segmentation in Patients with Severe Aortic Valve Disease by Elza Abdessater, Paniz Balali, Jimmy Pawlowski, Jérémy Rabineau, Cyril Tordeur, Vitalie Faoro, Philippe van de Borne, Amin Hossein

“…The proposed approach outperformed the existing methods, achieving a higher sensitivity and positive predictive value for S2, especially in the presence of severe heart murmurs. …”
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Application of artificial neural networks in the drilling processes: Can equivalent circulation density be estimated prior to drilling? by Husam H. Alkinani, Abo Taleb T. Al-Hameedi, Shari Dunn-Norman, David Lian

“…The goal of this work was to predict ECD prior to drilling by using artificial neural network (ANN). …”
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Estimating canopy height in tropical forests: Integrating airborne LiDAR and multi-spectral optical data with machine learning by Brianna J. Pickstone, Hugh A. Graham, Andrew M. Cunliffe

“…This study aims to compare the performance of three machine learning algorithms (Multiple Linear Regression (MLR), Random Forest (RF), and Convolutional Neural Networks (CNN)) when using PlanetScope and Sentinel-2 imagery to improve the accuracy of height predictions. …”
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Implementation of a neural network model in the Statistica 12 for mudflow frequency forecasting by B. A. Ashabokov, A. A. Tashilova, L. A. Kesheva, N. V. Teunova

“…It follows from the linear trend equation that, on average, over the entire period, including the predicted one, the number of mudflows tends to grow slightly by 0.3/10 years. …”
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Unsupervised machine learning identifies biomarkers of disease progression in post-kala-azar dermal leishmaniasis in Sudan. by Ana Torres, Brima Musa Younis, Samuel Tesema, Jose Carlos Solana, Javier Moreno, Antonio J Martín-Galiano, Ahmed Mudawi Musa, Fabiana Alves, Eugenia Carrillo

“…Today, basic knowledge of this neglected disease and how to predict its progression remain largely unknown.<h4>Methods and findings</h4>This study addresses the use of several biochemical, haematological and immunological variables, independently or through unsupervised machine learning (ML), to predict PKDL progression risk. …”
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Analysis of reservoir rock permeability changes due to solid precipitation during waterflooding using artificial neural network by Azizollah Khormali, Soroush Ahmadi, Aleksandr Nikolaevich Aleksandrov

“…A comparison of the predicted values of rock permeability under scaling conditions with experimental data showed that the proposed ANN model makes it possible to predict formation damage due to scaling with high accuracy. …”
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Komparasi Algoritma Support Vector Machines dengan Algoritma Artificial Neural Network untuk Memprediksi Nilai Persetujuan Kredit Modal Kerja yang Diberikan Bank Umum by Abu Sopian, Agus Wiyatno, Albert Riyandi

“…In this research will conducted working capital credit value approval prediction will be provided by commercial bank using support vector machine algorithm that is compared with artificial neutral network algorithm. …”
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On energy-balanced backpressure routing mechanisms for stochastic energy harvesting wireless sensor networks by Zheng Liu, Xinyu Yang, Peng Zhao, Wei Yu

“…Existing research efforts focus on the energy management based on the assumption that the energy harvesting process is predictable. Unfortunately, such an assumption is not practicable in real-world energy harvesting systems. …”
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AI-driven automated discovery tools reveal diverse behavioral competencies of biological networks by Mayalen Etcheverry, Clément Moulin-Frier, Pierre-Yves Oudeyer, Michael Levin

“…Many applications in biomedicine and synthetic bioengineering rely on understanding, mapping, predicting, and controlling the complex behavior of chemical and genetic networks. …”
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Beyond traditional methods: Innovative integration of LISS IV and Sentinel 2A imagery for unparalleled insight into Himalayan ibex habitat suitability. by Ritam Dutta, Lalit Kumar Sharma, Bheem Dutt Joshi, Vineet Kumar, Amira Sharief, Saurav Bhattacharjee, Mukesh Thakur, Dhriti Banerjee, Rajappa Babu

“…The Random Forest approach outperformed other algorithms in supervised classification techniques. …”
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