Renal failure in patients with hematological malignancies (literature review) by E. G. Gromova

“…The main reasons for the renal failure development in hematological cancer patients and syndromes that prevent adequate antitumor therapy are considered. Diagnostic algorithm optimization and supportive intensive care of acute renal failure is the key to the successful application of highly effective modern protocols of drug anticancer treatment.A special group is represented by patients suffering from monoclonal gammopathies with acute renal injury and hyperproduction of immunoglobulins free light chains. …”
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An Improved Low-Bit-Rate Image Compression Framework Based on Semantic-Aware Model and Neighborhood Attention by Chengbin Zeng, Liang Zhang

“…In addition, our proposed algorithm effectively mitigates distortions in facial and textual regions while preserving the structural integrity and visual fidelity. …”
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Development and Practice of Cloud Collaborative Platform for Downhole Measurement Tools by Che Yang, Yuan Guangjie, Qian Hongyu, Du Weiqiang, Wang Chenlong, Ding Jiping

“…In the paper， based on the remote operation requirements of coreless magnetic steering tool， a platform architecture of five modules， including simulation rehearsal， virtual training， remote operation， smart tool and intelligent decision， was designed in detail， achieving a whole process digitization from predrilling risk assessment and in-drilling acquisition and processing to post-drilling feedback and optimization， and a visual interface was developed. Moreover， to solve the problem of low far-field ranging accuracy， multiple magnetic steering data mining algorithms such as support vector machine （SVM）， decision tree （DT）， multilayer perceptron （MLP） and convolutional neural network （CNN） were built and compared， indicating that the robustness and generalization of the multilayer perceptron algorithm is the best. …”
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Numerical Solution of the Inverse Thermoacoustics Problem Using QFT and Gradient Method by Syrym E. Kasenov, Aigerim M. Tleulesova, Almas N. Temirbekov, Zholaman M. Bektemessov, Rysbike A. Asanova

“…The inverse problem was reduced to an optimization problem, where the objective function was minimized using gradient methods, including the accelerated Nesterov algorithm. …”
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A Data Resource Trading Price Prediction Method Based on Improved LightGBM Ensemble Model by Wan Nie, Bingliang Shen, Desheng Li

“…To address the key challenges of limited practical application, high implementation difficulty, and poor generalization capability in existing theoretical models for data resource pricing, this study employs generative adversarial network (GAN) to augment the dataset and constructs a DRV-LightGBM model based on a Bayesian parameter optimization algorithm that maximizes the coefficient of determination (<inline-formula> <tex-math notation="LaTeX">$R^{2}$ </tex-math></inline-formula>) to predict data resource transaction prices and provide post-hoc explanations for the prediction model. …”
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Improved deep learning model for accurate energy demand prediction and conservation in electric vehicles integrated with cognitive radio networks by V. Niranjani, Anandakumar Haldorai

“…To overcome this issue, this paper proposed a model of Empirical Mode Decomposition with CNN and optimized with Seagull Optimization Algorithm (EMD-CNN-SOA). …”
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Experimental and numerical investigation on thermal performance of enhanced geothermal system: A case study of Guanzhong basin by Guoyao Jin, Yuxiang Zhao, Ye Min, Xiao Zhang, Chao Jiang, Zijing Tan

“…A multi-objective genetic algorithm correlates operational variables with extraction efficiency, providing a quantitative framework for optimization. …”
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Research on the policy inconsistency, network motifs and low carbon effects for municipal solid waste management by Bo Lv, Tianxu Cui, Daiheng Li, Weiyue Yao

“…This study combines the policy consistency formula, a four-node network motif evolution algorithm, and the Exponential Random Graph Model (ERGM), analyzing MSWM green network motifs with carbon emission data. …”
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Voltage Support Capacity Improvement for Wind Farms with Reactive Power Substitution Control by Yuegong Li, Guorong Zhu, Jianghua Lu, Hua Geng

“…Considering differences in terminal voltage characteristics and operating conditions, this RPS control method employs a particle swarm optimization (PSO) algorithm to ensure that wind turbines can provide their optimal reactive power support capacity. …”
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Parametric Sensitivity Analysis of Safe Train Interval Model Based on Relative Braking Distance by QIAN Hua, LYU Haojiong

“…This study sought to analyze the sensitivity of key parameters affecting these safe intervals, to harness the potential of virtual coupling technology in improving efficiency while ensuring operational safety. The qualitative analysis based on a safe time interval model and the quantitative analysis based on simulations using the model plus an algorithm, were conducted, shedding light on the extent of influence from key parameters in the safe interval model on stopping time differences. …”
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Runoff Prediction and Uncertainty Analysis for Xijiang River Basin Based on CMIP6 Climate Scenarios by WU Huiming, YAN Meng, ZHOU Shuai

“…Based on this, the Xin'anjiang hydrological model (XAJ) is built, and the particle swarm optimization (PSO) algorithm is employed to calibrate and validate the model parameters. …”
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Game-based resource allocation in heterogeneous downlink CR-NOMA network without subchannel sharing by Deepa Das, Rajendra Kumar Khadanga, Deepak Kumar Rout, Md. Minarul Islam, Taha Selim Ustun

“…We frame this joint optimization of SU cluster formation and power allocation as a cooperative multi-armed bandit game. …”
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Evolution of Computer-Aided Process Planning for Hybrid Additive/Subtractive Process by Osama Abdulhameed, Abdulrahman Al-Ahmari, Syed Hammad Mian, Abdulmajeed Dabwan, Hisham Alkhalefah

“…Additionally, the genetic algorithm has been employed to obtain the best path with minimum inspection time. …”
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Contagious disease outbreaks: Distinguishing between constant and variable order using the SEIAR model by S.Sepehr Tabatabaei, Mohammadreza Dehghan

“…A heuristic approach is proposed for parameter estimation using a Genetic Optimization Algorithm, which evaluates all possible scenarios for the order and suggests parameter sets that perform well across these scenarios. …”
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Polymer electrolyte membrane fuel cell performance Revolutionized: Artificial intelligence-validated asymmetric flow channels enhance mass transport via hybrid analytical-numerical... by Nima Ahmadi, Ghader Rezazadeh

“…Experimental validation confirms a current density improvement of up to 5.6 % over conventional designs, while Artificial Intelligence (AI)-driven optimization via a hybrid Convolutional Neural Network and Genetic Algorithm independently identifies the same optimal configuration. …”
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Enhancing Power Allocation in DAS: A Hybrid Machine Learning and Reinforcement Learning Model by S. Gnanasekar, K. C. Sriharipriya

“…ML models utilize historical data to forecast optimal power levels, while MARL agents dynamically adjust power allocation based on real-time conditions, aiming to enhance spectral efficiency, minimize interference, and optimize energy efficiency. …”
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A model predictive control method for directional borehole trajectories in underground coal mines by Hao LI, Ningping YAO, Chengda LU, Jinbao ZHANG, Hongchao WEI, Jiajun WU, Jinyu LI

“…Finally, the control algorithm was validated using the drilling data from a coal mine in Hancheng City, Shaanxi Province. …”
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Dynamic spectrum allocation based on one-band multi-winner auction by Wen-zhu ZHANG, Ling-yun WANG

“…In order to improve the effectiveness of traditional auction in DSA (dynamic spectrum allocation) issue in cognitive radio networks,a new dynamic spectrum allocation algorithm based on one-band multi-winner auction was proposed.Compared with the original greedy algorithm,the new algorithm can achieve better spectrum allocation solutions with lower computational complexity by introducing the multiple greedy strategy.It increases the seller's revenue by improving the VCG (vickery-clarke-groves) mechanism,while retaining the dominant strategy incentive compatible property.In addition,it suppresses the occurrence of collusion effectively.Simulation results show that the algorithm proposed can get spectrum allocation efficiency close to the optimal solution and increase the auction revenue significantly.…”
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Application of Improved BQGA in Robot Kinematics Inverse Solution by Xiaoqing Lv, Ming Zhao

“…In addition, the improved algorithm further completes the anti-degradation mechanism, which maintains the diversity of the population while preserving the dominant gene to the maximum extent, so that the algorithm is not easy to fall into the local extremum and finally approaches the global optimal solution. …”
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Progressive Pruning of Light Dehaze Networks for Static Scenes by Byeongseon Park, Heekwon Lee, Yong-Kab Kim, Sungkwan Youm

“…Our progressive pruning algorithm, targeting a specific PSNR(Peak Signal-to-Noise Ratio) threshold, achieved optimal results at a certain pruning ratio, significantly reducing the number of channels in the target layer while maintaining PSNR above the threshold and preserving good structural similarity, before automatically stopping when performance dropped below the target. …”
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