Are conventional methods sufficient to calculate growth parameters of Pontastacus leptodactylus (Eschscholtz, 1823)? A case study of artificial intelligence from Keban Dam Lake by Benzer Semra, Benzer Recep

“…These measurements were analyzed using both the conventional length–weight relationship method and artificial neural networks. The results obtained using artificial neural networks and conventional methods were compared, and the analysis was based on MAPE and R2 performance criteria. …”
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Academic progress monitoring through neural network by Ramri Shukla, Bardia Khalilian, Sara Partouvi

“…Students are classified using artificial neural networks and random forests in this article. …”
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Reforming Real Estate Valuation for Financial Auditors With AI: An In-Depth Exploration of Current Methods and Future Directions by Silviu-Ionut BABTAN

“…This article examines several AI methods – Regression Models, Decision Trees, Random Forests, Artificial Neural Networks, and XGBoost – and explores their applications for improving property valuation accuracy and efficiency, with implications for other professions involved, e.g. audit. …”
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Crack Propagation Analysis Using Acoustic Emission Sensors for Structural Health Monitoring Systems by Zachary Kral, Walter Horn, James Steck

“…A novel method of implementing artificial neural networks and acoustic emission sensors to form a structural health monitoring (SHM) system for aerospace inspection routines was the focus of this research. …”
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Verification of Classification Model and Dendritic Neuron Model Based on Machine Learning by Dongbao Jia, Weixiang Xu, Dengzhi Liu, Zhongxun Xu, Zhaoman Zhong, Xinxin Ban

“…Artificial neural networks have achieved a great success in simulating the information processing mechanism and process of neuron supervised learning, such as classification. …”
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Barriers and enhance strategies for green supply chain management using continuous linear diophantine neural networks by Shougi S. Abosuliman, Saleem Abdullah, Nawab Ali

“…Abstract Artificial neural networks, a major element of machine learning, focus additional attention on the decision-making process. …”
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The classification of concentration of mixture of analytes using total principal component regression by Romas Baronas, Feliksas Ivanauskas, Robertas Paulauskas, Pranas Vaitkus

“…The results are compared with the results obtained using artificial neural networks. …”
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Forecasting Models for Time and Cost Performance Predicting of Infrastructural Projects by Aldhamad Saja Hadi Raheem, Maya Rana, Alazawy Suha Falih Mahdi, Alzwainy Faiq M.

“…The efficacy of residential property investment projects will be assessed through the implementation of models that incorporate Artificial Neural Networks and Multiple Linear Regression. Historical information of thirteen boundaries for twenty finished Private Property Venture Tasks were separated from the records of the Directorate of Lodging, then four models were created by utilizing Multiple Linear Regression strategy and Artificial Neural Networks method. …”
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The Control Data Method: A New Method of Modeling in Population Dynamics by Lin-Fei Nie, Zhi-Dong Teng

“…Using a the approximation property and the machine learning approach of artificial neural networks, a tuning algorithm of unknown parameters is obtained and the factual data of predator-prey can be asymptotically stabilized using a neural network controller. …”
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Consilience of Reductionism and Complexity Theory in Language Research: Adaptive Weight Model by Chao Zhang

“…This paper starts by discussing the adaptability of complex dynamic systems and combines cognitive processing model and artificial neural networks to construct and verify an adaptive weight model, showing that the study of reductionism is induction of high-weight elements and the study of complexity theory is a discussion of system complexity from adaptability, meaning that there is a good fit between the two frameworks. …”
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Spatial analysis of hyperspectral images for detecting adulteration levels in bon-sorkh (Allium jesdianum L.) seeds: Application of voting classifiers by Golshid Fathi, Seyed Ahmad Mireei, Mehrnoosh Jafari, Morteza Sadeghi, Hassan Karimmojeni, Majid Nazeri

“…After image preprocessing using median blur and bilateral filters, pixel-wise classification models were developed using artificial neural networks, random forest, and voting classifiers to detect pure bon-sorkh and shallot seeds. …”
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Desain Faktorial untuk Pembuktian Teori Masters dalam Penentuan Jumlah Lapisan dan Neuron Tersembunyi pada Peramalan Multivariat dengan Jaringan Syaraf Tiruan by Dwi Ayu Lusia, Awalludiyah Ambarwati

“…Accuracy of artificial neural networks is influenced by the number of hidden layers and neurons in them. …”
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Validation of Infinite Impulse Response Multilayer Perceptron for Modelling Nuclear Dynamics by F. Cadini, E. Zio, N. Pedroni

“…Artificial neural networks are powerful algorithms for constructing nonlinear empirical models from operational data. …”
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Detection and diagnosis of fault bearing using wavelet packet transform and neural network by Djaballah Said, Meftah Kamel, Khelil Khaled, Tedjini Mohsein, Sedira Lakhdar

“…This work is part of the diagnosis and classification of bearing defects by vibration analysis of signals from defective bearings using time domain and frequency analysis and wavelet packet transformations (Wavelet Packet Transform WPT) with Artificial Neural Networks (ANN). WPT is used for extracting defect indicators to train the neural classifier. …”
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Efficient Prediction of Network Traffic for Real-Time Applications by Muhammad Faisal Iqbal, Muhammad Zahid, Durdana Habib, Lizy Kurian John

“…Many predictors from three different classes, including classic time series, artificial neural networks, and wavelet transform-based predictors, are compared. …”
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Predicting the Pullout Capacity of Small Ground Anchors Using Nonlinear Integrated Computing Techniques by Mosbeh R. Kaloop, Jong Wan Hu, Emad Elbeltagi

“…The results of the developed models are compared with previous studies that used artificial neural networks and least square support vector machine techniques for the same case study. …”
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Use of Arduino for Monitoring the Air Quality of Indoor Environments by Felipe Macedo Freitas Siqueira, Lizandro de Sousa Santos

“…Another approach, based on artificial neural networks, was formulated in which the parameters were used as input arguments of the network and the TCI was used as a target parameter. …”
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Compressive Strength Prediction of Self-Compacting Concrete-A Bat Optimization Algorithm Based ANNs by Amir Andalib, Babak Aminnejad, Alireza Lork

“…This article examines the feasibility of using bat-trained artificial neural networks (ANNs) to predict the compressive strength of self-compacting concrete (SCC). …”
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Impact of earthquake�s epicenter distance on the failure of the embankment � A seismic prediction by Abdoullah Namdar, Omer Mughieda, Ts Haji Azahar Bin Mohd Yasin, Falak Azhar

“…The research adopted the numerical modeling method of soil categorized as a no-tensile material to explain displacement in selected points of the model using the extended finite element method (XFEM). Artificial Neural Networks (ANNs) were used to predict displacement obtained by XFEM. …”
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Crack simulation for the cover of the landfill � A seismic design by Mehran Karimpour-Fard, Omer Mughieda, Filippo Berto, Nurmunira Muhammad

“…Rankine�s theory and the Phantom Node Method were used for the simulation length of the crack and the mechanism of the crack propagation in the nonlinear extended finite element method (NXFEM). Artificial Neural Networks (ANNs) based on Levenberg-Marquardt Algorithm and Abalone Rings Data Set mode were used to predict displacement in critical points of the model. …”
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