Designing a Decision Support System (DSS) for Supplier Selection in Multiple Discount Environment by Marzieh Shahrezaee, Reza Ehtesham Rasi, Mehdi Seifbarghy

“…Outputs, which are, the selective suppliers and orders assigned to each of them are also to be considered by using Genetic Algorithm in MATLAB software for three parts in Emersan Company accordingly.…”
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Study on Tourism Development Using CRITIC Method for Tourist Satisfaction by Xi Yang, Noor Azman Ali, Huam Hon Tat

“…The integration of CRITIC, MLP, and GA provided a comprehensive framework that not only enhanced the accuracy of satisfaction evaluations but also optimized development strategies effectively. …”
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Robust Adaptive Fractional-Order PID Controller Design for High-Power DC-DC Dual Active Bridge Converter Enhanced Using Multi-Agent Deep Deterministic Policy Gradient Algorithm for... by Seyyed Morteza Ghamari, Daryoush Habibi, Asma Aziz

“…While these features make the DABC highly efficient, they also complicate controller design due to nonlinear behavior, fast switching, and sensitivity to component variations. …”
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Predicting Student Performance through Machine Learning Methods: Naive Bayesian Classifier by Chenyang Li, Qianzhi Zhou, Luming Du, Sihan Zhang

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SGD-TripleQNet: An Integrated Deep Reinforcement Learning Model for Vehicle Lane-Change Decision by Yang Liu, Tianxing Yang, Liwei Tian, Jianbiao Pei

“…This method integrates three types of deep Q-learning networks (DQN, DDQN, and Dueling DDQN) and uses the Stochastic Gradient Descent (SGD) optimization algorithm to dynamically adjust the network weights. …”
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Advanced methodology for maximum torque point tracking of hybrid excitation PMSM for EVs by Mahmoud M. Elymany, Nadia A. Elsonbaty, Aymen FLah, Lukas Prokop, Habib Kraiem, Mohamed A. Enany, Ahmed A. Shaier

“…This approach extends the constant power (CP) region by a 4.2:1 ratio. The manuscript also introduces a detailed mathematical model, considering both iron core losses and their impact on the EV profile. …”
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Design and Optimization of a Robust Wide‐Area Damping Controller for Mitigating Inter‐Area Oscillations in Wind‐Integrated Power Systems by Mehrdad Ahmadi Kamarposhti, Hassan Shokouhandeh, Sun‐Kyoung Kang, Ilhami Colak, El Manaa Barhoumi

“…The study also looks into how time delays, changes in wind speed, and load variations affect the effectiveness of the controller. …”
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Computational approaches in drug chemistry leveraging python powered QSPR study of antimalaria compounds by using artificial neural networks by Wakeel Ahmed, Tamseela Ashraf, Maliha Tehseen Saleem, Emad E. Mahmoud, Kashif Ali, Shahid Zaman, Melaku Berhe Belay

“…In this study we utilized machine learning algorithms namely Artificial Neural Networks and Random Forest to predict physiochemical characteristics of Anti-malaria drugs. …”
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Method on intrusion detection for industrial internet based on light gradient boosting machine by Xiangdong HU, Lingling TANG

“…Intrusion detection is a critical security protection technology in the industrial internet, and it plays a vital role in ensuring the security of the system.In order to meet the requirements of high accuracy and high real-time intrusion detection in industrial internet, an industrial internet intrusion detection method based on light gradient boosting machine optimization was proposed.To address the problem of low detection accuracy caused by difficult-to-classify samples in industrial internet business data, the original loss function of the light gradient boosting machine as a focal loss function was improved.This function can dynamically adjust the loss value and weight of different types of data samples during the training process, reducing the weight of easy-to-classify samples to improve detection accuracy for difficult-to-classify samples.Then a fruit fly optimization algorithm was used to select the optimal parameter combination of the model for the problem that the light gradient boosting machine has many parameters and has great influence on the detection accuracy, detection time and fitting degree of the model.Finally, the optimal parameter combination of the model was obtained and verified on the gas pipeline dataset provided by Mississippi State University, then the effectiveness of the proposed mode was further verified on the water dataset.The experimental results show that the proposed method achieves higher detection accuracy and lower detection time than the comparison model.The detection accuracy of the proposed method on the gas pipeline dataset is at least 3.14% higher than that of the comparison model.The detection time is 0.35s and 19.53s lower than that of the random forest and support vector machine in the comparison model, and 0.06s and 0.02s higher than that of the decision tree and extreme gradient boosting machine, respectively.The proposed method also achieved good detection results on the water dataset.Therefore, the proposed method can effectively identify attack data samples in industrial internet business data and improve the practicality and efficiency of intrusion detection in the industrial internet.…”
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Analisis Sentimen: Pengaruh Jam Kerja Terhadap Kesehatan Mental Generasi Z by Muhammad Daffa Al Fahreza, Ardytha Luthfiarta, Muhammad Rafid, Michael Indrawan

“…The influence of working hours also contributes to the mental health of this generation. …”
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Improved Confidence-Interval Estimations Using Uncertainty Measure and Weighted Feature Decisions for Cuff-Less Blood-Pressure Measurements by Soojeong Lee, Mugahed A. Al-antari, Gyanendra Prasad Joshi

“…The mean absolute error results were obtained by weighted feature determination combining GPR and gradient boosting algorithms (GBA) for SBP (1.46 mmHg) and DBP (0.69 mmHg). …”
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Using Segment Anything Model 2 for Zero-Shot 3D Segmentation of Abdominal Organs in Computed Tomography Scans to Adapt Video Tracking Capabilities for 3D Medical Imaging: Algorithm... by Yosuke Yamagishi, Shouhei Hanaoka, Tomohiro Kikuchi, Takahiro Nakao, Yuta Nakamura, Yukihiro Nomura, Soichiro Miki, Takeharu Yoshikawa, Osamu Abe

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Multi-Objective Optimization of Energy Storage Station Configuration in Power Grids Considering the Flexibility of Thermal Load Control by Kaikai Wang, Yao Wang, Jin Gao, Yan Liang, Zhenfei Ma, Hanyue Liu, Zening Li

“…The proposed model was solved using the POA-GWO-CSO optimization algorithm to achieve the optimal energy storage deployment and cost efficiency. …”
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Predicting Landing Position Deviation in Low-Visibility and Windy Environment Using Pilots’ Eye Movement Features by Xiuyi Li, Yue Zhou, Weiwei Zhao, Chuanyun Fu, Zhuocheng Huang, Nianqian Li, Haibo Xu

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Automatic Synthesis of Recurrent Neurons for Imitation Learning From CNC Machine Operators by Hoa Thi Nguyen, Roland Olsson, Oystein Haugen

“…They yield error rates 270% lower for the first operation action, while the error rates are 20% lower for the second action. We also show that our evolutionary algorithm is capable of creating skip-connections and gating mechanisms adapted to the specific characteristics of our dataset.…”
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A High-Resolution Spectral Analysis Method Based on Fast Iterative Least Squares Constraints by Yanyan Ma, Haixia Kang, Weifeng Luo, Yunxiao Zhang, Lintao Luo

“…Based on this, we propose a least squares constrained spectral analysis method using a greedy fast shrinkage algorithm. This method replaces the traditional Tikhonov regularization objective function with an L1-norm regularized objective function and employs a greedy fast shrinkage algorithm. …”
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A Corn Point Cloud Stem-Leaf Segmentation Method Based on Octree Voxelization and Region Growing by Qinzhe Zhu, Ming Yu

“…In this paper, we present an algorithm that addresses the shortcomings of traditional methods in complex agricultural environments. …”
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GPU-Accelerated Fock Matrix Computation with Efficient Reduction by Satoki Tsuji, Yasuaki Ito, Haruto Fujii, Nobuya Yokogawa, Kanta Suzuki, Koji Nakano, Victor Parque, Akihiko Kasagi

“…To address this issue, we propose a parallel algorithm that efficiently and suitably distributes the atomic operations; and significantly reduces the memory contention by decomposing the Fock matrix into multiple replicas, allowing each GPU thread to contribute to different replicas. …”
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Enhancing Agricultural Futures Return Prediction: Insights from Rolling VMD, Economic Factors, and Mixed Ensembles by Yiling Ye, Xiaowen Zhuang, Cai Yi, Dinggao Liu, Zhenpeng Tang

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Machine-learning based optimizing the neutronic and thermal-hydraulic performance in a VVER-1000 mixed-core as well as fuel burnup assessment by A. Koraniany, G.R. Ansarifar

“…By integrating this neural network with a genetic algorithm, optimization was carried out to identify the optimal fuel placement and enrichment for loading the UTVS fuel assembly into the targeted reactor core. …”
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