DRBO—A Regional Scale Simulator Calibration Framework Based on Day-to-Day Dynamic Routing and Bayesian Optimization by Xuan Jiang, Yibo Zhao, Chonghe Jiang, Junzhe Cao, Alexander Skabardonis, Alex Kurzhanskiy, Raja Sengupta

“…Based on the decomposition, the DRBO framework uses iterative algorithms to find the best dynamic combinations. It utilizes the Bayesian optimization and day-to-day routing update to separately calibrate the dynamic, then combine them sequentially in an iterative way. …”
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A Cooperative GNSS Vector-DLL (CoVDLL) Method for Multiple UAVs Positioning by Chuntao Li, Xinru Wang, Changhui Jiang, Zikang Su, Shoubin Chen, Yuwei Chen

“…To optimize navigation solution estimation in the CoVDLL, a Factor Graph Optimization (FGO) algorithm is employed to realize the navigation solution’s optimal estimation. …”
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Unboxing Tree ensembles for interpretability: A hierarchical visualization tool and a multivariate optimal re-built tree by Giulia Di Teodoro, Marta Monaci, Laura Palagi

“…The interpretability of models has become a crucial issue in Machine Learning because of algorithmic decisions' growing impact on real-world applications. …”
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Optimizing Tumor Detection in Brain MRI with One-Class SVM and Convolutional Neural Network-Based Feature Extraction by Azeddine Mjahad, Alfredo Rosado-Muñoz

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Advancing mmWave Altimetry for Unmanned Aerial Systems: A Signal Processing Framework for Optimized Waveform Design by Maaz Ali Awan, Yaser Dalveren, Ali Kara, Mohammad Derawi

“…This article addresses challenges arising from radial velocity due to UAS descent rates and terrain variation through theoretical and mathematical approaches for characterization and mandatory compensation. While constant false alarm rate (CFAR) algorithms have been reported for ground detection, a comparison of their variants within the scope UAS altimetry is limited. …”
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Optimizing photocatalytic dye degradation: A machine learning and metaheuristic approach for predicting methylene blue in contaminated water by Yunus Ahmed, Keya Rani Dutta, Sharmin Nahar Chowdhury Nepu, Meherunnesa Prima, Hamad AlMohamadi, Parul Akhtar

“…This work points out the possibility of taking complete advantage of advanced machine learning algorithms along with metaheuristics optimization in improving photocatalytic processes, hence opening a bright avenue for real applications in water treatment.…”
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Optimizing spatial normalization of multisubject inner ear MRI: comparison of different geometry-preserving co-registration approaches by Johannes Gerb, Valerie Kirsch, Emilie Kierig, Thomas Brandt, Marianne Dieterich, Rainer Boegle

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Multiclass Fault Diagnosis in Power Transformers Using Dissolved Gas Analysis and Grid Search-Optimized Machine Learning by Andrew Adewunmi Adekunle, Issouf Fofana, Patrick Picher, Esperanza Mariela Rodriguez-Celis, Oscar Henry Arroyo-Fernandez, Hugo Simard, Marc-André Lavoie

“…Grid search optimization was employed to fine-tune the hyperparameters of each model, while model evaluation was conducted using 10-fold cross-validation and six performance metrics. …”
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Remaining useful life prediction of a small sample of aero-engine based on an improved gray Markov model by Dong-hai Li, Ji-liang Tu, Hui Liu, Nai-zhi Liao

“…To enhance adaptability, a genetic algorithm dynamically optimizes the time response parameters of the grey model, overcoming the limitation of a fixed structure in traditional methods. …”
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Generative design recommendations for the historical Mardiṅ High School and Gaziṗaşa Primary School buildings, Turkey by Mizgin Gökçe Salık, Fatma Demet Aykal

“…The genetic algorithm (GA) is inspired by natural selection, emphasizing the survival of the fittest. …”
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Brain age prediction from MRI images based on a convolutional neural network with MRMR feature selection layer by Mustafa Hatem Al Ghariri, Seyed Omid Shahdi

“…The feature selection layer uses MRMR algorithm which identifies essential characteristics for a target variable while minimizing feature redundancy to select the optimal feature subset. …”
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A dimension reduction assisted credit scoring method for big data with categorical features by Tatjana Miljkovic, Pei Wang

“…The evidence suggests that even small improvements in the accuracy of existing credit-scoring models may optimize profits while effectively managing risk exposure. …”
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Broadcasting in Stars of Cliques and Path-Connected Cliques by Akash Ambashankar, Hovhannes A. Harutyunyan

“…Determining the broadcast time for a node in an arbitrary network is NP-complete. While polynomial-time algorithms exist for specific network topologies, the problem remains open for many others. …”
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Convolutional neural networks for accurate estimation of canopy cover by F. Puig, R. Gonzalez Perea, A. Daccache, M.A. Soriano, J.A. Rodríguez Díaz

“…Deploying an RGB camera across various crops (wheat, alfalfa, and sweet pepper) in Spain and California, we harnessed a dataset comprising 283,000 images, each with dimensions of 256 × 256 pixels, for network training. Optimizing the neural network was achieved through a Genetic Algorithm (GA), employing an objective function focused on minimizing parameter density while maintaining accuracy. …”
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Bayesian Network-Based Landslide Susceptibility Safe Route Assessment in the Face of Uncertain Knowledge and Various Information by Xinyu Gao, Bo Wang, Wen Dai, Yuanmin Liu

“…In this study, we propose an integrated framework that combines a Bayesian network (BN)-based landslide susceptibility map (LSM) with an improved A* algorithm for safe and efficient route planning. The BN model effectively integrates multi-source data and uncertainty knowledge to generate an accurate LSM, while the improved A* algorithm combines safety and efficiency considerations to optimize routes. …”
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Runtime–Coherence Tradeoffs for Hybrid Satisfiability Solvers by Vahideh Eshaghian, Soren Wilkening, Johan Aberg, David Gross

“…Finally, we present numerical simulations, which suggest additional flexibility in implementing hybrid algorithms with the optimal tradeoff.…”
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‌Rockburst intensity grading prediction based on the LOF-ENN-KNN model‌ by Haoran Ge, Jiyong Zhang, Congbo Ma, Kai Hui, Yicong Li, Ziniu Wu

“…Through the comparison and exploration of different sampling methods and different combinations of LOF algorithm, single resampling technology (SMOTE, ADASYN) or simple technology superposition (LOF-SMOTE, LOF-ADASYN) is easy to introduce over-fitting or negative coupling effect, while LOF-ENN-KNN significantly improves the robustness and generalization ability of the model through modular design. …”
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Direction of Arrival (DOA) Estimation Using a Deep Unfolded Learned Iterative Shrinkage Thresholding Algorithm (LISTA) Network in a Non-Uniform Metasurface by Xinyi Niu, Xiaolong Su, Lida He, Guanchao Chen

“…To address these issues, we optimize a non-uniform metasurface array to reduce hardware costs and mutual coupling effects while enhancing resolution. …”
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Localization of Sensor Nodes in 3D Wireless Sensor Networks with a Single Anchor by an Improved Adaptive Artificial Bee Colony (iaABC) Algorithm by Dursun Ekmekci, Hüseyin Altınkaya

“…The method employs the Improved Adaptive Artificial Bee Colony (iaABC) algorithm, a model of the classical ABC algorithm. …”
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Hybrid-driven modeling using a BiLSTM–AdaBoost algorithm for diameter prediction in the constant diameter stage of Czochralski silicon single crystals by Yu-Yu Liu, Ding Liu, Shi-Hai Wu, Yi-Ming Jing

“…Subsequently, the prediction results of the BiLSTM network are weighted and fused by the AdaBoost algorithm to obtain the final time series prediction output, and the prediction performance is further enhanced by iterative optimization. …”
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