Application of Genetic Algorithms to Solve MTSP Problems with Priority (Case Study at the Jakarta Street Lighting Service) by Sugih Sudharma Tjandra, Fran Setiawan, Hanoum Salsabila

“…In its development based on actual events in the real world, some priorities must be visited first in optimizing vehicle routes. Several studies on MTSP and CVRP models have been conducted with exact solutions and algorithms. …”
Get full text

Metaheuristics in automated machine learning: Strategies for optimization by Francesco Zito, El-Ghazali Talbi, Claudia Cavallaro, Vincenzo Cutello, Mario Pavone

“…We examine various metaheuristic algorithms employed and, in particular, their effectiveness in improving model performance across diverse applications. …”
Get full text

Privacy protection risk identification mechanism based on automated feature combination by CAI Minchao, YAO Hongwei, WANG Yang, QIN Zhan, CHEN Shaomeng, REN Kui

“…In practice, the anomaly detection (AD) algorithm usually faced technical challenges such as difficulty in optimizing feature combinations, difficulty in improving classifier accuracy, and low model application efficiency. …”
Get full text

Elastic Momentum-Enhanced Adaptive Hybrid Method for Short-Term Load Forecasting by Wenting Zhao, Haoran Xu, Peng Chen, Juan Zhang, Jing Li, Tingting Cai

“…The particle swarm optimization (PSO) algorithm is improved by adjusting its elastic momentum, and the enhanced APSO algorithm is employed to optimize the adaptive weights of the hybrid model. …”
Get full text

A Ｒeinforcement Learning of Cloud Ｒesource Scheduling Algorithm Based on Adaptive Weight by LI Cheng-yan, SUN Wei, TANG Li-min

“…We considered the cloud computing resource scheduling problem，and proposed a multi-objective optimization mathematical model to optimize task completion time and running cost simultaneously. …”
Get full text

Progressive filling partitioning and mapping algorithm for Spark based on allocation fitness degree by Chen BIAN, Jiong1 YU, Wei-rong XIU, Bin LIAO, Chang-tian YING, Yu-rong QIAN

“…The job execution mechanism of Spark was analyzed,task efficiency model and Shuffle model were established,then allocation fitness degree (AFD) was defined and the optimization goal was put forward.On the basis of the model definition,the progressive filling partitioning and mapping algorithm (PFPM) was proposed.PFPM established the data distribution scheme adapting Reducers’ computing ability to decrease synchronous latency during Shuffle process and increase cluster the computing efficiency.The experiments demonstrate that PFPM could improve the rationality of workload distribution in Shuffle and optimize the execution efficiency of Spark.…”
Get full text

Simulation of automatic intrusion detection in university networks by using neural network algorithms by Houdun Xu

“…Using appropriate training methods and optimization algorithms, train and optimize the neural network model to achieve high accuracy and robustness. …”
Get full text

Research on International Law Data Integrity Guarantee Based on Antiterrorism Prediction Algorithm by Huang Ru Qing

“…In order to improve the quality of international law data, this paper designs a method to ensure the integrity of international law data based on an antiterrorism prediction algorithm. …”
Get full text

A New LQR Optimal Control for a Single-Link Flexible Joint Robot Manipulator Based on Grey Wolf Optimizer by Navid Razmjooy, Mehdi Ramezani, Ali Namadchian

“…By considering the proposed performance index and comparing with the PSO-based controller as a popular algorithm, the superiority of the proposed LQR controller in improving the stability and performance of the manipulator is shown. …”
Get full text

Deep learning-based feature selection for detection of autism spectrum disorder by Ibrahim Nafisah, Nermine Mahmoud, Ahmed A. Ewees, Mohamed G. Khattap, Abdelghani Dahou, Safar M. Alghamdi, Ibrahim A. Fares, Mohammed Azmi Al-Betar, Mohammed Azmi Al-Betar, Mohamed Abd Elaziz, Mohamed Abd Elaziz

“…Feature selection is enhanced through an optimized Hiking Optimization Algorithm (HOA) that integrates DynamicOpposites Learning (DOL) and Double Attractors to improve convergence toward the optimal subset of features.ResultsThe proposed model is evaluated using multiple ASD datasets. …”
Get full text

Bio inspired feature selection and graph learning for sepsis risk stratification by D. Siri, Raviteja Kocherla, Sudharshan Tumkunta, Pamula Udayaraju, Krishna Chaitanya Gogineni, Gowtham Mamidisetti, Nanditha Boddu

“…To further improve predictive accuracy, the TOTO metaheuristic algorithm is applied for model fine-tuning. …”
Get full text

Guided Particle Swarm Optimization for Feature Selection: Application to Cancer Genome Data by Simone A. Ludwig

“…It involves selecting a subset of relevant features for use in model construction. Feature selection helps in improving model performance by reducing overfitting, enhancing generalization, and decreasing computational cost. …”
Get full text

Traffic safety evaluation of emerging mixed traffic flow at freeway merging area considering driving behavior by Yaqin He, Dingshan Xiang, Daobin Wang

“…First, human drivers’ driving behaviors were classified into aggressive driving, normal driving, and conservative driving using a k-means clustering algorithm based on field dataset analysis. Next, an improved lane-changing model of HDVs, accounting for driving behavior, was developed by incorporating lane-changing duration and a lane-changing motivation function within a multi-objective optimization framework. …”
Get full text

Combined use of near infrared spectroscopy and chemometrics for the simultaneous detection of multiple illicit additions in wheat flour by Xinyi Dong, Ying Dong, Jinming Liu, Siting Wu

“…Compared to regression models built with competitive adaptive reweighted sampling and genetic algorithm for feature wavelength selection, the performance improved significantly, enhancing generalization capability. …”
Get full text

Classification-based point cloud denoising and 3D reconstruction of roadways by Denghong CHEN, Ning PANG, Wen NIE, Juqiang FENG, Jiliang KAN, Jinjing ZHANG

“…Meanwhile, the existing 3D reconstruction algorithms suffer from low modeling accuracy and high susceptibility to distortion. …”
Get full text

Algorithm study of digital HPA predistortion using one novel memory type BP neural network by Chun-hui HUANG, Yong-jie WEN

“…Based on the characteristic analysis of the high power amplifier (HPA) in wide-band CMMB repeater stations,a novel neural network was proposed which can respectively process the memory effect and the nonlinear of power amplifier.The novel model based on real-valued time-delay neural networks(RVTDNN) uses the Levenberg-Marquardt (LM) optimization to iteratively update the coefficients of the neural network.Due to the new parameters w⁰in the novel NN model,the modified formulas of LM algorithm were provided.Next，in order to eliminate the over-fitting of LM algorithm,the Bayesian regularization algorithm was applied to the predistortion system.Additionally,the predistorter of CMMB repeater stations based on the indirect learning method was constructed to simulate the nonlinearity and memory effect of HPA.Simulation results show that both the NN models can improve system performance and reduce ACEPR (adjacent channel error power ratio ) by about 30 dB.Moreover,with the mean square error less than 10⁻⁶,the coefficient of network for FIR-NLNNN is about half of that for RVTDNN.Similarly,the times of multiplication and addition in the iterative process of FIR-NLNNN are about 25% of that for RVTDNN.…”
Get full text

Design of OFDM-IM system based on IRS-assisted by Mengmeng ZHAO, Liming HE, Fangfang LIU

“…Index modulation (IM) and intelligent reflecting surface (IRS) are emerging mobile communication technologies.In order to improve the reliability of traditional orthogonal frequency division multiplexing (OFDM) system, an orthogonal frequency division multiplexing with index modulation (OFDM-IM) system based on IRS-assisted was designed.Firstly, the OFDM-IM system was designed by using spatial modulation and frequency domain modulation to increase the Euclidean distance between subcarriers.Then, by establishing an equivalent circuit model, a practical IRS model was obtained.Finally, an alternating optimization algorithm was used to optimize the active transmission power of the access point (AP) and passive beamforming of the IRS jointly.The simulation results show that compared to the benchmark scheme, the symbol error rate (SER) or bit error rate (BER) of the OFDM-IM system based on IRS-assisted can be reduced by 60%～90%.Especially in the case of high signal-to-noise ratio, the SER or BER of the system can reach 1.0×10^-6, which indicates that the introduction of IM and IRS technologies has optimized the link transmission quality of end-to-end communication system.In addition, based on the IRS-assisted OFDM-IM system as the standard, simulations are conducted to demonstrate the impact of various parameters from the IRS model and IM.It concludes that the parameters in the system should be selected reasonably according to channel state information (CSI).…”
Get full text

Optimal distributed generation placement and sizing using modified grey wolf optimization and ETAP for power system performance enhancement and protection adaptation by Nasreddine Bouchikhi, Fethi Boussadia, Riyadh Bouddou, Ayodeji Olalekan Salau, Saad Mekhilef, Chaima Gouder, Sarra Adiche, Abdallah Belabbes

“…The MGWO algorithm is an improved version of the conventional GWO algorithm, which is based on a hierarchical model inspired by the social behavior of grey wolves. …”
Get full text

Fan Blade Crack Detection Algorithm Based on Multi-Scale Feature Fusion by Yongjun Qi, Hailin Tang, Altangerel Khuder

Get full text

Sustainable closed-loop supply chain network design: heuristic hybrid approach with considering inflation and carbon emission policies by Saeid Kalantari, Hamed Kazemipoor, Farzad Movahedi Sobhani, Seyyed Mohammad Hadji Molana

“…Also, due to the complexity of the model and its multi-objective, a new combined method of Heuristic algorithm (HA) and Multi-Choice Goal Programming with Utility Function (MCGP-UF) is used. …”
Get full text