Komparasi Machine Learning Berbasis Pso Untuk Prediksi Tingkat Keberhasilan Belajar Berbasis E-Learning by Elin Panca Saputra, Siti Nurajizah, Mawadatul Maulidah, Nadiyah Hidayati, Taufik Rahman

“…Maka dari itu dapat disimpulkan penerapan menggunakan algoritma Naïve Bayes(NB) berbasis PSO mendapatkan hasil kenerja dengan bobot sebesar 94.40% dan angka AUC sebesar 94.50%, berikutnya Algoritma Support Vectore Machine(SVM) Berbasis PSO dengan hasil kinerja akurasi sebesar 88.20 dan nilai AUC seberar 91.10%, dan Artificial Neural Network(NN) berbasis Particle Swarm Optimizatio(PSO) menghasilkan skor hasil kinerja akurasi dengan bobot 99.20% dan nilai akurasi sebesar 98.50%, maka Artificial Neural Network(NN)  berbasis PSO memiliki keunggulan lebih besar dari pada algoritma naïve bayer berbasis PSO dan Support Vector Machine(SVM) dengan PSO. …”
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Tourism Growth Prediction Based on Deep Learning Approach by Xiaoling Ren, Yanyan Li, JuanJuan Zhao, Yan Qiang

“…The outcome of this study showed that the performance of the adopted deep learning framework was better than that of artificial neural network and support vector regression models. …”
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MODELING OF SOLAR RADIATION WITH A NEURAL NETWORK by VALENTIN STOYANOV, IVAYLO STOYANOV, TEODOR ILIEV

“… Modeling of solar radiation with neural network could be used for real-time calculations of the radiation on tilted surfaces with different orientations. In the artificial neural network (ANN), latitude, day of the year, slope, surface azimuth and average daily radiation on horizontal surface are inputs, and average daily radiation on tilted surface of definite orientation is output. …”
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An Intelligent System for Load Forecasting on a Distribution Network by Saheed Gbadamosi, Ojo Olukayode Adedayo

“…This technique is an integrated system consisting of fuzzy logic systems and Artificial Neural network (ANN). The inputs to the system include days of the week, temperature, time, current and previous hourly load on the distribution network. …”
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Channel modeling of molecular communication via free diffusion with multiple receiver by Zhuo SUN, Xu BAO, Jie LIN, Wence ZHANG

“…A coexistence scenario with a point source, a pair of absorbing and transparent receiver was considered, an interference factor was introduced in the proposed channel model based on the receiving molecular probability in the transparent receiver considering the influences of the absorbing receiver on the transparent one.Furthermore, the channel model of point source and transparent receiver had been proposed by using Levenberg-Marquardt algorithm combined with artificial neural network to study and predict channel model parameters.The simulation results not only verify the effectiveness of the proposed channel model, but also show that the peak time of any point in the environment is directly proportional to the square of the distance from the point source to the receiver, and inversely proportional to the molecular diffusion coefficient, and the peak time is not affected by the absorbing receiver in the environment.…”
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Forecasting-Aided Monitoring for the Distribution System State Estimation by S. Carcangiu, A. Fanni, P. A. Pegoraro, G. Sias, S. Sulis

“…In this paper, an innovative approach based on an artificial neural network (ANN) load forecasting model to improve the distribution system state estimation accuracy is proposed. …”
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Predicting the Hall-Petch slope of magnesium alloys by machine learning by Bo Guan, Chao Chen, Yunchang Xin, Jing Xu, Bo Feng, Xiaoxu Huang, Qing Liu

“…Two machine learning models, artificial neural network (ANN) and random forest (RF), were built and validated using 138 data. …”
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Flexural Strength Prediction of Welded Flange Plate Connections Based on Slenderness Ratios of Beam Elements Using ANN by Amir A. Hedayat, Ehsan Jazebi, Saman AsadAbadi, Amin Iranpour

“…Proposed theoretical formulas and artificial neural network- (ANN-) based models developed in this study were able to adequately predict the connection strength.…”
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Prediction of groundwater level Sharif Abad catchment of Qom using WANN and GP models

“…To compare the results of the hybrid model of wavelet analysis-neural network (WNN), genetic programming (GP) multiple linear regression (MLR) and artificial neural network (ANN), two criteria of root mean squared error (RMSE) and nash-sutcliffe coefficient of efficiency (E) is used. …”
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Predictive Modeling of Fracture Behavior in Ti6Al4V Alloys Manufactured by SLM Process by Mohsen Sarparast, Majid Shafaie, Mohammad Davoodi, Ahmad Memaran Babakan, Hongyan Zhang

“…The research explores the impact of Artificial Neural Network (ANN) architecture, specifically hidden layers and neurons, on predicting fracture parameters. …”
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Forecasting Directions, Dates, And Causes of Future Technological Revolutions concerning the Growth of Human Capital by Ning Chen, Masoud Vaseei, Ali Peivandizadeh

“…Next, research gaps were analyzed by using the artificial neural network clustering method and also by analyzing covered and uncovered compounds. …”
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Estimating Compressive Strength of High Performance Concrete with Gaussian Process Regression Model by Nhat-Duc Hoang, Anh-Duc Pham, Quoc-Lam Nguyen, Quang-Nhat Pham

“…Based on experimental outcomes, prediction results of the GPR model are superior to those of the Least Squares Support Vector Machine and the Artificial Neural Network. Furthermore, GPR model is strongly recommended for estimating HPC strength because this method demonstrates good learning performance and can inherently express prediction outputs coupled with prediction intervals.…”
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Dynamics of specialization in neural modules under resource constraints by Gabriel Béna, Dan F. M. Goodman

“…Using a simple, toy artificial neural network setup that allows for precise control, we find that structural modularity does not in general guarantee functional specialization (across multiple measures of specialization). …”
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ANN Synthesis Model of Single-Feed Corner-Truncated Circularly Polarized Microstrip Antenna with an Air Gap for Wideband Applications by Zhongbao Wang, Shaojun Fang

“…A computer-aided design model based on the artificial neural network (ANN) is proposed to directly obtain patch physical dimensions of the single-feed corner-truncated circularly polarized microstrip antenna (CPMA) with an air gap for wideband applications. …”
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Simulated Annealing Based Hybrid Forecast for Improving Daily Municipal Solid Waste Generation Prediction by Jingwei Song, Jiaying He, Menghua Zhu, Debao Tan, Yu Zhang, Song Ye, Dingtao Shen, Pengfei Zou

“…A simulated annealing (SA) based variable weighted forecast model is proposed to combine and weigh local chaotic model, artificial neural network (ANN), and partial least square support vector machine (PLS-SVM) to build a more accurate forecast model. …”
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Application research on the time–frequency analysis method in the quality detection of ultrasonic wire bonding by Wuwei Feng, Xin Chen, Cuizhu Wang, Yuzhou Shi

“…Finally, an artificial neural network was built to recognize and detect the quality of ultrasonic wire bonding. …”
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Segmentation and Classification of Vowel Phonemes of Assamese Speech Using a Hybrid Neural Framework by Mousmita Sarma, Kandarpa Kumar Sarma

“…This paper describes an Artificial Neural Network (ANN) based algorithm developed for the segmentation and recognition of the vowel phonemes of Assamese language from some words containing those vowels. …”
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Neural Network Assisted Inverse Dynamic Guidance for Terminally Constrained Entry Flight by Hao Zhou, Tawfiqur Rahman, Wanchun Chen

“…In order to ensure terminal velocity constraint, a prediction of the terminal velocity is required, based on which, the approximated Bézier curve is adjusted. An artificial neural network is used for this prediction of the terminal velocity. …”
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Predictive modeling and optimization of SI engine performance and emissions with GEM blends using ANN and RSM by Farooq Shaik, D. Vinay Kumar, N. Channa Keshava Naik, G. Radha Krishna, T. M. Yunus Khan, Abdul Saddique Shaik, Abdulrajak Buradi, Addisu Frinjo Emma

“…Abstract The study employed an Artificial Neural Network (ANN) to predict the performance and emissions of a single-cylinder SI engine using blends of Gasoline, Ethanol, and Methanol (GEM) ranging from E10 to E50 equivalence, achieving less than 5% error compared to experimental values. …”
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MODELLING ROUNDABOUT ENTRY CAPACITY FOR MIXED TRAFFIC FLOW USING ANN: A CASE STUDY IN INDIA by Aarohi Kumar MUNSHI, Ashish Kumar PATNAIK

“…This study attempts to develop models for roundabout entry capacity by applying Artificial Neural Network (ANN) analysis for mixed traffic flow conditions. …”
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