Neural-Driven heuristic for strip packing trained with Black-Box optimization by Mariusz Kaleta, Tomasz Śliwiński

“…Unlike conventional heuristics, our approach dynamically adapts placement decisions based on a broad set of features describing the current partial solution and remaining items. Through extensive computational experiments, we compare our method against well-known strip packing heuristics, including MaxRects and Skyline-based algorithms. …”
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Edge connectivity of a neutrosophic graph by Aparna Tripathy, Amaresh Chandra Panada, Siva Prasad Behera, Bhabani S. Mohanty

“…We develop efficient algorithms that minimize computational overhead and ensure accuracy in identifying the critical edge sets. …”
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Reducing PAPR in NOMA Waveforms Using Genetic-Enhanced PTS and SLM: A Low-Complexity Approach for Improved throughput, power spectral density, and Power Efficiency by Arun Kumar, Nishant Gaur, Aziz Nanthaamornphong

“…Current hybrid solutions, such as Genetic Algorithm (GA)-based optimization, provide better performance but are still computationally intensive. …”
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Multi-resource joint management strategy for 5 G network slicing based on POMDP by Yale Li

“…Furthermore, the model employs a hybrid heuristic value iterative algorithm to optimize computational efficiency, reduce network latency, improve throughput, and enhance resource utilization. …”
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Numerical investigation for optimizing thermal performance of Al2O3-TiO2/water hybrid nanofluid: An artificial neural network approach based on Levenberg–Marquardt algorithm by Khalid Arif, Syed Tauseef Saeed, Talha Anwar, Shajar Abbas, Muhammad Nauman Aslam

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Multi-objective optimization and characteristic analysis of contra-rotating fan double-row blades coupling by Xinyu ZHANG, Hua JIANG, Wuqi GONG

“…To enhance the aerodynamic performance of contra-rotating fan and ensure the safe working environment of mine, based on feedforward neural network agent model and genetic algorithm, the multi-objective optimization of contra-rotating fan double-row blades coupling is carried out. …”
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Propagation characteristics of stress waves induced by underground blasting under the influence of rock-soil interfaces by Xianzhong Meng, Chuanbo Zhou, Nan Jiang, Zhen Zhang, Yumin Yang, Di Wu

“…Therefore, the vibration field caused by cylindrical charge blasting in elastic rock and partial-saturation poro-viscoelastic soil was solved. …”
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Advanced Frequency Analysis of Signals with High-Frequency Resolution by Patrik Flegner, Ján Kačur, Milan Durdán, Marek Laciak, Rebecca Frančáková

“…As part of this scientific research, the issues of frequency zoom were thoroughly addressed, solving the partial problems of this algorithm, both in theory and in the context of signal theory.…”
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Modeling Spatial Data with Heteroscedasticity Using PLVCSAR Model: A Bayesian Quantile Regression Approach by Rongshang Chen, Zhiyong Chen

“…We apply a Bayesian quantile regression (BQR) of the partially linear varying coefficient spatial autoregressive (PLVCSAR) model for spatial data to improve the prediction of performance. …”
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Evaluating Maize Residue Cover Using Machine Learning and Remote Sensing in the Meadow Soil Region of Northeast China by Zhengwei Liang, Jia Du, Weilin Yu, Kaizeng Zhuo, Kewen Shao, Weijian Zhang, Cangming Zhang, Jie Qin, Yu Han, Bingrun Sui, Kaishan Song

“…The Google Earth Engine (GEE) and remote sensing images from 2019 to 2023 were used to obtain spectral characteristics before the maize seedling stage in Northeast China, followed by constructing the CRC estimation models using machine learning algorithms. To avoid the impact of multicollinearity among data, three machine learning algorithms—ridge regression (RR), partial least squares regression (PLSR), and least absolute shrinkage and selection operator (LASSO)—were employed. …”
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Towards a complete classification of holographic entropy inequalities by Ning Bao, Keiichiro Furuya, Joydeep Naskar

“…Thus, by virtue of the argued completeness of the contraction map proof method, the problem of finding all holographic entropy inequalities is equivalent to the problem of finding all contraction maps, which we translate to a problem of finding all image graph partial cubes. We give an algorithmic solution to this problem and characterize the complexity of our method. …”
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Water quality index modelling and its application on artificial intelligence (AI) in conjunction with machine learning (ML) methodologies for mapping surface water potential zones... by Abhijeet Das

“…The main causes of this decrease include inappropriate home waste disposal practices, the release of partially or completely untreated sewage, and industrial effluents into nearby bodies of water that are connected to river systems. …”
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Global Maximum Power Point Tracking of Photovoltaic Systems Using Artificial Intelligence by Rukhsar, Aidha Muhammad Ajmal, Yongheng Yang

“…Traditional maximum power point tracking (MPPT) algorithms have several drawbacks on tracking the global maximum power point (GMPP) under partial shading conditions (PSCs). …”
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Prediction of pulmonary embolism by an explainable machine learning approach in the real world by Qiao Zhou, Ruichen Huang, Xingyu Xiong, Zongan Liang, Wei Zhang

“…To address this, we employed an artificial intelligence–based machine learning algorithm (MLA) to construct a robust predictive model for PE. …”
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Design of Ricker Wavelet Neural Networks for Heat and Mass Transport in Magnetohydrodynamic Williamson Nanofluid Boundary-Layer Porous Medium Flow with Multiple Slips by Zeeshan Ikram Butt, Muhammad Asif Zahoor Raja, Iftikhar Ahmad, Muhammad Shoaib, Rajesh Kumar, Syed Ibrar Hussain

“…The solver employs a hybrid approach that combines genetic algorithms, serving as a global search method, with sequential quadratic programming, which functions as a local optimization technique. …”
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Prediction and Mapping of Soil Total Nitrogen Using GF-5 Image Based on Machine Learning Optimization Modeling by LIU Liqi, WEI Guangyuan, ZHOU Ping

“…Three machine learning algorithms were introduced: Partial least squares regression (PLSR), backpropagation neural network (BPNN), and support vector machine (SVM) driven by a polynomial kernel function (Poly). …”
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Generation of shortest path search dataflow networks of actors for parallel multi-core implementation by A. A. Prihozhy

“…The objective is to improve performance of parallel implementations of algorithms which have the property of partial order of computations on multicore processors.Methods. …”
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Verification of Backtracking and Branch and Bound Design Templates by N. V. Shilov

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DIAGNOSTIC SYSTEM FOR OPTIMIZING THE DIESEL LOCOMOTIVE COOLING MODES by V.P. Perevertov, N.K. Yurkov, N.V. Chertykovtseva, V.N. Novikova, N.A. Kuzin

“…The software is written in C++ with partial use of the assembler language. Results and conclusions. …”

Half-hourly electricity price prediction model with explainable-decomposition hybrid deep learning approach by Sujan Ghimire, Ravinesh C. Deo, Konstantin Hopf, Hangyue Liu, David Casillas-Pérez, Andreas Helwig, Salvin S. Prasad, Jorge Pérez-Aracil, Prabal Datta Barua, Sancho Salcedo-Sanz

“…Input features are identified using the Partial Autocorrelation Function , and models are optimized using the Optuna algorithm. …”
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