MULTI-MODEL STACK ENSEMBLE DEEP LEARNING APPROACH FOR MULTI-DISEASE PREDICTION IN HEALTHCARE APPLICATION by Bhaskar Adepu, T. Archana

“…This model integrates pre-processing techniques and employs the Tuna Swarm Optimization (TSO) Algorithm for feature selection in executing multi-label disease prediction. …”
Get full text

Adaptive gradient scaling: integrating Adam and landscape modification for protein structure prediction by Vitalii Kapitan, Michael Choi

“…Despite their success, machine learning methods face fundamental limitations in optimizing complex high-dimensional energy landscapes, which motivates research into new methods to improve the robustness and performance of optimization algorithms. …”
Get full text

Research on IoT network performance prediction model of power grid warehouse based on nonlinear GA-BP neural network by Pang Lele, Xia Bo, Cheng Zhanfeng, Ren Zhiqiang, Shen Hao, Li Pengfei

“…This study introduces a novel approach for forecasting network performance prediction in power grid warehouses, employing a nonlinear Genetic Algorithm (GA)-optimized backpropagation (BP) neural network model. …”
Get full text

Correlation learning based multi-task model and its application by XU Wei, LUO Jianping, LI Xia, CAO Wenming

“…The experimental results verify the effectiveness of the proposed multi-task learning model based on the correlation layer. Meanwhile, the proposed multi-task learning network as a proxy model is applied to the Bayesian optimization algorithm, which not only reduces the evaluation times of model to target problem, but also enlarges the number of training data exponentially and further improves the model accuracy.…”
Get full text

Explainable AutoML models for predicting the strength of high-performance concrete using Optuna, SHAP and ensemble learning by Muhammad Salman Khan, Tianbo Peng, Tianbo Peng, Muhammad Adeel Khan, Asad Khan, Mahmood Ahmad, Mahmood Ahmad, Kamran Aziz, Mohanad Muayad Sabri Sabri, N. S. Abd EL-Gawaad

“…This study introduces four explainable Automated Machine Learning (AutoML) models that integrate Optuna for hyperparameter optimization, SHapley Additive exPlanations (SHAP) for interpretability, and ensemble learning algorithms such as Random Forest (RF), Extreme Gradient Boosting (XGB), Light Gradient Boosting Machine (LGB), and Categorical Gradient Boosting (CB). …”
Get full text

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. …”
Get full text

Simplifying the calibration of ecological models by using the parameter estimation tool (PEST): The Curonian Lagoon case by Burak Kaynaroglu, Mindaugas Zilius, Rasa Idzelytė, Artūras Razinkovas-Baziukas, Georg Umgiesser

“…However, subjective and time-consuming manual (trial-and-error) calibration methods cannot ensure optimal parameter match.To address this, we automated the calibration of a newly developed ecological model to improve the simulation of nutrient dynamics as ammonia, nitrate, and phosphate in the estuarine system (Curonian Lagoon). …”
Get full text

Development of IIOT-Based Pd-Maas Using RNN-LSTM Model with Jelly Fish Optimization in the Indian Ship Building Industry by PNV Srinivasa Rao, PVY Jayasree

“…The validation of the proposed predictive maintenance model optimization with different types of deep learning algorithms shows that our proposed methodology gives an improved accuracy of 98.9336% which is higher than any other models.   …”
Get full text

Enhancing Last-Mile Logistics: AI-Driven Fleet Optimization, Mixed Reality, and Large Language Model Assistants for Warehouse Operations by Saverio Ieva, Ivano Bilenchi, Filippo Gramegna, Agnese Pinto, Floriano Scioscia, Michele Ruta, Giuseppe Loseto

“…However, existing approaches often treat these aspects in isolation, missing opportunities for optimization and operational efficiency gains through improved information visibility across different roles in the logistics workforce. …”
Get full text

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. …”
Get full text

A Dual-Strategy Framework for Cyber Threat Detection in Imbalanced, High-Dimensional Data Across Heterogeneous Networks by T. Saranya, S. Indra Priyadharshini

“…Second, the Cauchy-Gaussian Genetic-Arithmetic Optimizer (CG-GAO) addresses the challenge of high-dimensional data by combining a genetic algorithm (GA) and an arithmetic optimization algorithm (AOA), enhancing exploration and preventing premature convergence. …”
Get full text

Optimization of fractional PI controller parameters for enhanced induction motor speed control via indirect field-oriented control by I. I. Alnaib, A. N. Alsammak

“…The novelty of the work consists of a proposal for a driving cycle model for testing the control system of electric vehicles in Mosul City (Iraq), and using a Complex Fractional Order Proportional Integral (CFOPI) controller to control IMs via IFOC strategies, the Artificial Bee Colony (ABC) algorithm was applied, which is considered to be highly efficient in finding the values of controllers. …”
Get full text

Predicting suicidal behavior outcomes: an analysis of key factors and machine learning models by Mohammad Bazrafshan, Kourosh Sayehmiri

“…A combination of statistical models for feature selection and machine learning algorithms for prediction was used, with Random Forest showing the best performance. …”
Get full text

Improving Acceptance to Sensory Substitution: A Study on the V2A-SS Learning Model Based on Information Processing Learning Theory by Kyeong Deok Moon, Yun Kyung Park, Moo Seop Kim, Chi Yoon Jeong

“…This improvement is significantly higher than the gain of 2.72% achieved by optimizing the V2A-SS algorithm with Mel-Scaled Frequency Mapping. …”
Get full text

Accurate irrigation decision-making of winter wheat at the filling stage based on UAV hyperspectral inversion of leaf water content by Xuguang Sun, Baoyuan Zhang, Menglei Dai, Cuijiao Jing, Kai Ma, Boyi Tang, Kejiang Li, Hongkai Dang, Limin Gu, Wenchao Zhen, Xiaohe Gu

“…The SPA algorithm also improved the inversion efficiency of LWC. …”
Get full text

Evolutionary fuzzy learning for Chinese medicine liver syndrome differentiation by Jia-Yu Yan, Peng-Wei Zhang, Wei-Guo Sheng, Jun-Ping Shi, Wei Ni, Li Li, Yu-Jun Zheng

“…To determine the most appropriate fuzzy membership functions of the fuzzy learning machines, an evolutionary algorithm was employed to optimize the types and parameters of the fuzzy functions simultaneously. …”
Get full text

Matching and Control Optimisation of Variable-Geometry Turbochargers for Hydrogen Fuel Cell Systems by Matt L. Smith, Alexander Fritot, Davide Di Blasio, Richard Burke, Tom Fletcher

Get full text

LM-CNN-based Automatic Cost Calculation Model for Power Transmission and Transformation Projects by Xiaolin WU, Ling LUAN, Lianwu PAN, Hailong LI

“…Finally, in view of the big difference between the expected output and the actual output, the Levenberg-Marquart algorithm is utilized to optimize the weight parameters of the convolutional neural network to complete the model training. …”
Get full text

Optimizing wind energy conversion system efficiency using advanced modified super-twisting direct power control: Real-time implementation on dSPACE 1104 board by Mourad Yessef, Habib Benbouhenni, Ahmed Lagrioui, Youness El Mourabit, Nicu Bizon, Ilhami Colak, Badre Bossoufi, Ayman Alhejji

Get full text

Analysis of Customer Power Consumption Behavior Based on DPSO-Kmeans under the Ubiquitous Power Internet of Things by WANG Ying, XIANG Wen, ZHANG Qun, GAO Xiuyun

Get full text