Financial fraud detection using a hybrid deep belief network and quantum optimization approach by Gui Yu, Zhenlin Luo

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A New Approach to Environmental Economic Dispatch Using Multiobjective Differential Evolution: A Case Study by Carine Nogueira Santino, Jorge Laureano Moya Rodriguez, Cristiano Hora De Oliveira Fontes

“…This paper presents a new modeling approach which consists of using a hyperbolic function to predict generation costs. …”
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Energy management for microgrids integrating renewable sources and hybrid electric vehicles by Wanying Liu, Chunqing Rui, Zilin Liu, Jinxin Chen

“…KOA models candidate solutions as planetary positions, continuously updating them relative to the optimal solution for comprehensive domain exploration. …”
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Enhancing Compressive Strength Prediction in Recycled Aggregate Concrete through Robust Hybrid Machine Learning Approaches by Samuel Keown, Dylan O’Dwyer

“…To address this issue, robust hybrid machine learning (ML) approaches are employed, particularly emphasizing the Least Square Support Vector Regression (LSSVR) model. This investigation explores the integration of LSSVR with two innovative optimizers, namely the Giant Trevally Optimizer (GTO) and the Dingo Optimization Algorithm (DOA). …”
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Study on Subway Station Street Block-Level Land Use Pattern and Plot Ratio Control Based on Machine Learning by Mingyi Kuang, Fei Fu, Fangzhou Tian, Liwei Lin, Can Du, Yuesong Zhang

“…This study takes Panda Avenue Subway Station as a case study to analyze the evolution of land use patterns around subway stations and explore optimization strategies to enhance land development efficiency and spatial utilizationTo fill this research gap, this paper proposes a CNN-AIMatch model based on machine learning algorithm and an enhanced PLUS-Markov prediction model using the increase and decrease of floor area ratio as a control measure, which adopts an increase in plot ratio as a control measure to improve the accuracy of the Kappa coefficient in different plot ratio scenarios and the prediction of 3D urban spatial growth trends. …”
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A simulation-driven computational framework for adaptive energy-efficient optimization in machine learning-based intrusion detection systems by Ripal Ranpara, Osamah Alsalman, Om Prakash Kumar, Shobhit K. Patel

“…Extensive simulations conducted on the KDD 1999 dataset demonstrate that GreenMU achieves a detection accuracy close to 99%, significantly surpassing standard baseline models while reducing energy consumption by 31%. Furthermore, the framework improves computational efficiency, reducing processing time by 15% and making it highly effective for resource-constrained environments such as IoT and edge computing. …”
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Artificial intelligence-optimized shield parameters for soft ground tunneling in urban environment: A case study of Bangkok MRT Blue Line by Sahatsawat Wainiphithapong, Chana Phutthananon, Sompote Youwai, Pitthaya Jamsawang, Phattarawan Malaisree, Ochok Duangsano, Pornkasem Jongpradist

“…For simplification and practical field implementation, the same set of SOP values is applied across all 11 timesteps during the optimization process. Using the proposed optimization framework, the optimal results demonstrate improvements in Pavg, increasing by up to 109.8% (from 13.99 to 29.35 mm) and in S, reducing up to 79.6% (from 34.55 to 7.06 mm) when MOO is conducted as a time series using the simplified method. …”
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White Shark Optimization for Solving Workshop Layout Optimization Problem by Bin Guo, Yuanfei Wei, Qifang Luo, Yongquan Zhou

“…Using a real–world case study, the White Shark Optimizer (WSO) algorithm is applied to solve the model. …”
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Development of a machine learning-based surrogate model for friction prediction in textured journal bearings by Yujun Wang, Georg Jacobs, Shuo Zhang, Benjamin Klinghart, Florian König

“…This enhancement is achieved through an architecture design based on cross-validation and further optimization utilizing the genetic algorithm. Eventually, the average prediction accuracy is improved to 98.81% from 95.89%, with the maximum error reduced to 3.25% from 13.17%. …”
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Dynamic optimization of solar DG and shunt capacitor placement to mitigate the impact of EV charging stations on power distribution network by T. Yuvaraj, M. Thirumalai, T.D. Suresh, Sudhakar Babu Thanikanti, Mohammad Khishe

“…Simulation results confirm the superior performance of QRSMA in improving voltage profiles, reducing power losses, and achieving better computational efficiency compared to conventional optimization algorithms. …”
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Enhanced early detection of dysarthric speech disabilities using stacking ensemble deep learning model by Jagat Chaitanya Prabhala, Ravi Ragoju, Venkatanareshbabu Kuppili, Christophe Chesneau

“…Unlike conventional stacking methods that use fixed meta-classifiers, this study employs a Genetic Algorithm (GA)-based optimization strategy to dynamically determine optimal weight contributions of the base models, enhancing classification robustness and adaptability.The preprocessing pipeline converts speech signals from the time domain to the frequency domain by using a Short-Time Fourier Transform (STFT). …”
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Hybrid A*-Guided Model Predictive Path Integral Control for Robust Navigation in Rough Terrains by Joonyeol Yang , Minhyeong Kang , Seulchan Lee, Sanghyun Kim

“…This article proposes the Hybrid A*-guided Model Predictive Path Integral (MPPI) algorithm augmented with traversability estimation to address the challenges of path planning on uneven terrains. …”
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Text intelligent correction in English translation: A study on integrating models with dependency attention mechanism. by Yutong Liu, Shile Zhang

“…The research uses the Conference on Natural Language Learning (CoNLL)-2014 dataset as an experimental benchmark, which contains a rich collection of grammatical error samples and is a standard resource in linguistic research. During model training, the Adam optimization algorithm is employed, and the model's performance is enhanced by introducing a customized dependency self-attention mechanism for parameter optimization. …”
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Dynamic Reactive Power Optimization Strategy for AC/DC Hybrid Power Grid Considering Different Wind Power Penetration Levels by Nan Feng, Yuyao Feng, Yun Su, Yajun Zhang, Tao Niu

“…Considering the nonlinearity and non-convexity of the optimization model, trajectory sensitivity method and whale optimization algorithm are adopted to enhance the solution efficiency. …”
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Efficient and Stable Learning for Distribution Network Operation: A Model-Based Reinforcement Learning Approach by Dong Yan, Zhan Shi, Xinying Wang, Yiying Gao, Tianjiao Pu, Jiye Wang

“…This study introduces a reward evaluation system to assess the effectiveness of various strategies and proposes an enhanced algorithm based on the Model-based DRL approach. Incorporating a state transition model, the proposed algorithm augments data and enhances dynamic deduction, improving training efficiency. …”
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Recurrent Neural Network-Based Model Predictive Control for Multiple Unmanned Quadrotor Formation Flight by Boyang Zhang, Xiuxia Sun, Shuguang Liu, Xiongfeng Deng

“…The RNN-based MPC is proposed for each subsystem, where the RNN is introduced as the predictive model in MPC. And to improve the modeling accuracy, an adaptive updating law is developed to tune weights online for the RNN. …”
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EDECO: An Enhanced Educational Competition Optimizer for Numerical Optimization Problems by Wenkai Tang, Shangqing Shi, Zengtong Lu, Mengying Lin, Hao Cheng

“…On the one hand, the estimation of distribution algorithm enhances the global exploration ability and improves the population quality by establishing a probabilistic model based on the dominant individuals provided by EDECO, which solves the problem that the algorithm is unable to search the neighborhood of the optimal solution. …”
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Smart indoor monitoring for disabled individuals using an ensemble of deep learning models in an IoT environment by Faisal S. Alsubaei, Abdulrahman A. Alshdadi, Mohammed Rizwanullah

“…Initially, the SIMDP-EDLIoT approach uses linear scaling normalization (LSN) to ensure that the input data is scaled appropriately. Besides, the Improved Osprey Optimization Algorithm (IOOA)-based feature selection is employed to classify the most relevant features, enhancing the efficiency of the system by reducing dimensionality. …”
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Building Information Modelling- (BIM-) Based Generative Design for Drywall Installation Planning in Prefabricated Construction by Jose Daniel Cuellar Lobo, Zhen Lei, Hexu Liu, Hong Xian Li, SangHyeok Han

“…This study proposes a generative design approach that utilizes the optimization of the drywall installation layout to improve overall project efficiency. …”
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Query scheduling based on cloud-edge multi-data warehouse architecture and cost prediction model by GAO Xuning, YANG Song, LI Mingzhe, ZHANG Yanfeng

“…The scheduling framework and optimization algorithm achieve significant performance improvement on SSB and TPC-DS datasets. …”
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