Enhancing Lidar-Based 3D Classification Through an Improved Deep Learning Framework With Residual Connections by Shih-Lin Lin, Jun-Yi Wu

Get full text

A Framework for Low-Carbon Container Multimodal Transport Route Optimization Under Hybrid Uncertainty: Model and Case Study by Fenling Feng, Fanjian Zheng, Ze Zhang, Lei Wang

“…Subsequently, a multi-strategy improved whale optimization algorithm (WOA) is developed to solve the formulated model. …”
Get full text

A Genetic algorithm aided hyper parameter optimization based ensemble model for respiratory disease prediction with Explainable AI. by Balraj Preet Kaur, Harpreet Singh, Rahul Hans, Sanjeev Kumar Sharma, Chetna Sharma, Md Mehedi Hassan

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. …”
Get full text

Tramp Ship Routing and Scheduling with Integrated Carbon Intensity Indicator (CII) Optimization by Haiying Yang, Feiyang Ren, Jingbo Yin, Siqi Wang, Rafi Ullah Khan

“…This study addresses the tramp ship routing and scheduling problem by incorporating the carbon intensity indicator (CII) into the optimization framework. A bi-objective optimization model is developed, with two objective functions aimed at maximizing fleet profit and improving CII ratings. …”
Get full text

Predictive Modeling of Yoga's Impact on Venous Clinical Severity Scoring Using Gaussian Process Classification and Advanced Optimization Algorithms by Yazdan Ashgevari, Faranak Kazemi

“…The study employs the Adaptive Opposition Slime Mould Algorithm (AOSM) and Mountain Gazelle Optimizer (MGO) to enhance the predictive capabilities of a Gaussian Process Classification (GPC) model. …”
Get full text

The Application Based on Support Vector Machine Optimized by Particle Swarm Optimization and Genetic Algorithm by MAN Chun-tao, LIU Bo, CAO Yong-cheng

“…In order to improve the precision of the parameter optimization, the research integrates the Particle Swarm Optimization Algorithm with Support Vector Machine, and matches the experimental data, and then establishes a steadystate model of complex process system, which is based on Particle Swarm Optimization Algorithm and Support Vector Machine On the basis of this model, an improved Particle Swarm Optimization Algorithm introduced to Genetic Algorithm is proposed, in order to overcome the defects of Particle Swarm. …”
Get full text

Optimizing Equivalent Property-Damage-Only (EPDO) Prediction Models with Genetic Algorithms: A Case Study on Roundabout Geometric Characteristics by Hossein Samadi, Omid Rahmani, Khaled Shaaban, Amir Saman Abdollahzadeh Nasiri, Mehrzad Hasanvand

Get full text

An artificial neural network and Levenberg-Marquardt training algorithm-based mathematical model for performance prediction by Farheen Bano, Suhail H. Serbaya, Ali Rizwan, Mohammad Shabaz, Faraz Hasan, Hany S. Khalifa

Get full text

Fitting membrane resistance along with action potential shape in cardiac myocytes improves convergence: application of a multi-objective parallel genetic algorithm. by Jaspreet Kaur, Anders Nygren, Edward J Vigmond

“…Performance was compared to a genetic algorithm using only AP morphology data. The optimal parameter sets and goodness of fit as computed by the different methods were compared. …”
Get full text

Ultrahigh-Dimensional Model and Optimization Algorithm for Resource Allocation in Large-Scale Intelligent D2D Communication System by Minxin Liang, Jiandong Liu, Jinrui Tang, Ruoli Tang

“…Simulation results show that the developed VGCC-PSO algorithm performs the best in optimizing the UHDO model with up to 6000 dimensionalities. …”
Get full text

Low Capillary Elastic Flow Model Optimization Using the Lattice Boltzmann Method and Non-Dominated Sorting Genetic Algorithm by Yaqi Hou, Wei Zhang, Jiahua Hu, Feiyu Gao, Xuexue Zong

“…This paper establishes an LBM multiphase flow model enhanced by machine learning. The hyperparameters of the machine learning model are optimized using the particle swarm algorithm. …”
Get full text

Optimization of artificial intelligence in localized big data real-time query processing task scheduling algorithm by Maojin Sun, Luyi Sun

“…This research not only improves the efficiency of task processing, but also provides new ideas for optimizing future scheduling algorithms.…”
Get full text

A fuzzy based chicken swarm optimization algorithm for efficient fault node detection in Wireless Sensor Networks by B Nagarajan, Santhosh Kumar SVN, M Selvi, K Thangaramya

“…In the course of this effort, an effective strategy for sensor node failure detection algorithm using the Poisson Hidden Markov Model (PHMM) and the Fuzzy-based Chicken Swarm Optimization (F-CSO) is proposed for efficient detection of sensor node faults in the WSN. …”
Get full text

Dissolved Oxygen Prediction Based on SOA-SVM and SOA-BP Models by ZHANG Xuekun

“…To improve the accuracy of dissolved oxygen prediction,this paper researches and proposes a prediction method that combines seagull optimization algorithm (SOA) with support vector machine (SVM) and BP neural network,prepares four prediction schemes based on the monthly dissolved oxygen monitoring data of the Jinghong Power Station in Xishuangbanna,a national important water supply source in Yunnan Province,from January 2009 to September 2020,optimizes the key parameters of SVM and weight threshold of BP neural network by SOA to construct SOA-SVM and SOA-BP models,predicts the dissolved oxygen of Jinghong Power Station based on the models,and compares the prediction results with those of SVM and BP models.The results show that:The absolute values of the average relative errors of the SOA-SVM and SOA-BP models for the 4 schemes of dissolved oxygen prediction are between 4.07%~4.98% and 3.85%~4.83%,and that of the average absolute errors are 0.309~0.374 mg/L and 0.294~0.371 mg/L,respectively.With better prediction accuracy than SVM and BP models,they have good prediction accuracy and generalization ability.SOA can effectively optimize the key parameters of SVM and weight threshold of BP neural network.SOA-SVM and SOA-BP models are feasible for dissolved oxygen prediction,which can provide references for related prediction research.…”
Get full text

Research on Oil Well Production Prediction Based on GRU-KAN Model Optimized by PSO by Bo Qiu, Jian Zhang, Yun Yang, Guangyuan Qin, Zhongyi Zhou, Cunrui Ying

“…First, the MissForest algorithm is employed to handle anomalous data, improving data quality. …”
Get full text

Enhanced securities investment strategy using ISSA–SVM: a hybrid model combining adaptive moving average, support vector machine, and multi-strategy sparrow search algorithm for im... by Wei Ni, Qingqing Chen, Xiaochen Guo, Yanan Liu

“…This study proposes a novel hybrid strategy, ISSA–SVM, that combines Adaptive Moving Average (AMA), Support Vector Machine (SVM), and an Improved Sparrow Search Algorithm (ISSA) to enhance CTA model performance in securities investment. …”
Get full text

Hierarchical Deep Learning Model Optimization Using Enhanced Evolutionary-based Approach for Fake News Detection by Deepti Nikumbh, Anuradha Thakare

“…This work introduces the Deep Learning Model with Evolutionary Computing Approach (DLECA), a novel method for compressing and optimizing hierarchical deep learning models (HDLM). …”
Get full text

Improvement in positional accuracy of neural-network predicted hydration sites of proteins by incorporating atomic details of water-protein interactions and site-searching algorith... by Kochi Sato, Masayoshi Nakasako

“…Here, we report the improvements in prediction accuracy by the reorganized CNN together with the details in the architecture, training data, and peak search algorithm.…”
Get full text

Improved firefly algorithm–extended Kalman filter–least-square support-vector machine voltage sag monitoring and classification method based on edge computing by Zhu Liu, Xuesong Qiu, Yonggui Wang, Shuai Zhang, Zhi Li

“…Extract characteristic quantities such as average value, duration of sag, minimum sag dispersion characteristics, number of sag phases, and flow direction of disturbance energy. As a model training data set, the least-square support-vector machine method optimized based on the improved firefly algorithm is used to create a multi-level classification model of voltage sag source to realize the classification of voltage sag sources. …”
Get full text

Multiphase Transport Network Optimization: Mathematical Framework Integrating Resilience Quantification and Dynamic Algorithm Coupling by Linghao Ren, Xinyue Li, Renjie Song, Yuning Wang, Meiyun Gui, Bo Tang

“…Next, we create a dynamic adaptive public transit optimization model using an entropy weight-TOPSIS decision framework coupled with an improved simulated annealing algorithm (ISA-TS), achieving coordinated suburban–urban network optimization while maintaining 92.3% solution stability under simulated node failure conditions. …”
Get full text