The Role of Artificial Neural Networks in Prediction of Mechanical and Tribological Properties of Composites—A Comprehensive Review
Published 2022 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
The Role of Artificial Neural Networks in Prediction of Mechanical and Tribological Properties of Composites—A Comprehensive Review
Authors
Keywords
-
Journal
ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
Volume -, Issue -, Pages -
Publisher
Springer Science and Business Media LLC
Online
2022-02-01
DOI
10.1007/s11831-021-09691-7
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Analysing wear behaviour of Al–CaCO3 composites using ANN and Sugeno-type fuzzy inference systems
- (2020) A. A. Sosimi et al. NEURAL COMPUTING & APPLICATIONS
- Extract interpretability-accuracy balanced rules from artificial neural networks: A review
- (2020) Congjie He et al. NEUROCOMPUTING
- Marine Application of Fiber Reinforced Composites: A Review
- (2020) Felice Rubino et al. Journal of Marine Science and Engineering
- Preparation, characterization and antimicrobial activity of polyvinyl alcohol/gum arabic/chitosan composite films incorporated with black pepper essential oil and ginger essential oil
- (2020) Augustine Amalraj et al. INTERNATIONAL JOURNAL OF BIOLOGICAL MACROMOLECULES
- Neural network‐based energy management of multi‐source (battery/UC/FC) powered electric vehicle
- (2020) Huseyin A. Yavasoglu et al. INTERNATIONAL JOURNAL OF ENERGY RESEARCH
- Artificial neural network technique to predict dynamic fracture of particulate composite
- (2020) Vinod Kushvaha et al. JOURNAL OF COMPOSITE MATERIALS
- Prediction of composite microstructure stress-strain curves using convolutional neural networks
- (2020) Charles Yang et al. MATERIALS & DESIGN
- The Number of Confirmed Cases of Covid-19 by using Machine Learning: Methods and Challenges
- (2020) Amir Ahmad et al. ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
- Hidden representations in deep neural networks: Part 2. Regression problems
- (2020) Laya Das et al. COMPUTERS & CHEMICAL ENGINEERING
- A biological image classification method based on improved CNN
- (2020) Jiaohua Qin et al. Ecological Informatics
- Mechanical behaviour and microscopic analysis of epoxy and E-glass reinforced banyan fibre composites with the application of artificial neural network and deep neural network for the automatic prediction of orientation
- (2020) Suraj Shyam et al. JOURNAL OF COMPOSITE MATERIALS
- A recurrent neural network–based model for predicting bending behavior of ionic polymer–metal composite actuators
- (2020) Hojat Zamyad et al. JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES
- CNN-based image recognition for topology optimization
- (2020) Seunghye Lee et al. KNOWLEDGE-BASED SYSTEMS
- Practical artificial neural network tool for predicting the axial compression capacity of circular concrete-filled steel tube columns with ultra-high-strength concrete
- (2020) Viet-Linh Tran et al. THIN-WALLED STRUCTURES
- An integrated intrusion detection system using correlation‐based attribute selection and artificial neural network
- (2020) I. Sumaiya Thaseen et al. Transactions on Emerging Telecommunications Technologies
- An Artificial Neural Network Approach to Predicting Most Applicable Post-Contract Cost Controlling Techniques in Construction Projects
- (2020) Temitope Omotayo et al. Applied Sciences-Basel
- Prediction of wear properties of graphene-Si3N4 reinforced titanium hybrid composites by artificial neural network
- (2020) Tugba Mutuk et al. Materials Research Express
- Experimental investigation and prediction of tribological behavior of unidirectional short castor oil fiber reinforced epoxy composites
- (2020) Rajesh Egala et al. Friction
- Enhanced toughness in ceramic-reinforced polymer composites with herringbone architectures
- (2020) Robert B. Zando et al. COMPOSITES SCIENCE AND TECHNOLOGY
- Experimental investigation of physical, thermal, hygral and mechanical properties of cementitious composites at high temperatures
- (2020) Kateřina Horníková et al. CONSTRUCTION AND BUILDING MATERIALS
- World competitive contest-based artificial neural network: A new class-specific method for classification of clinical and biological datasets
- (2020) Zohre Arabi Bulaghi et al. GENOMICS
- Prediction of load-displacement curve in a complex structure using artificial neural networks: A study on a long bone
- (2020) Hadi Rahmanpanah et al. INTERNATIONAL JOURNAL OF ENGINEERING SCIENCE
- Modelling of tribological responses of composites using integrated ANN-GA technique
- (2020) Santanu Sardar et al. JOURNAL OF COMPOSITE MATERIALS
- A comparative analysis of the abrasion wear characteristics of industrial wastes filled glass/polyester composites based on the design of experiment and neural network
- (2020) Subhrajit Ray et al. POLYMER COMPOSITES
- A Study on Mechanical and Tribological Properties of Aluminium 1100 Alloys 6% of RHAp, BAp, CSAp, ZnOp and Egg Shellp Composites by ANN
- (2020) A. Nagaraj et al. Silicon
- Processing and preparation of aerospace-grade aluminium hybrid metal matrix composite in a modified stir casting furnace integrated with mechanical supersonic vibration squeeze infiltration method
- (2020) Vasanthakumar Pandian et al. Materials Today Communications
- An online self-organizing modular neural network for nonlinear system modeling
- (2020) Junfei Qiao et al. APPLIED SOFT COMPUTING
- Predictive ANN models for varying filler content for cotton fiber/PVC composites based on experimental load displacement curves
- (2020) Monzure-Khoda Kazi et al. COMPOSITE STRUCTURES
- Study on deformation behavior in supercooled liquid region of a Ti-based metallic glassy matrix composite by artificial neural network
- (2020) Y.S. Wang et al. JOURNAL OF ALLOYS AND COMPOUNDS
- Tailoring composite materials for nonlinear viscoelastic properties using artificial neural networks
- (2020) Xianbo Xu et al. JOURNAL OF COMPOSITE MATERIALS
- Increasing the ductility of heat-resistant AlNp/Al composites by submicron Al2O3 particles
- (2020) Kewei Xie et al. MATERIALS CHARACTERIZATION
- Microstructural measurement and artificial neural network analysis for adhesion of tribolayer during sliding wear of powder-chip reinforcement based composites
- (2020) Mayank Agarwal et al. MEASUREMENT
- Study on tribological properties of a novel composite by filling microcapsules into UHMWPE matrix for water lubrication
- (2020) Zhenxiang Yang et al. TRIBOLOGY INTERNATIONAL
- Prediction of the reaction forces of spiral-groove gas journal bearings by artificial neural network regression models
- (2020) Elia Iseli et al. Journal of Computational Science
- An integrated artificial neural network and Taguchi approach to optimize the squeeze cast process parameters of AA6061/Al2O3/SiC/Gr hybrid composites prepared by novel encapsulation feeding technique
- (2020) L. Natrayan et al. Materials Today Communications
- Dry sliding wear characteristics evaluation and prediction of vacuum casted marble dust (MD) reinforced ZA-27 alloy composites using hybrid improved bat algorithm and ANN
- (2020) Swati Gangwar et al. Materials Today Communications
- An intelligent model for the prediction of the depth of the wear of cementitious composite modified with high-calcium fly ash
- (2020) Seweryn Malazdrewicz et al. COMPOSITE STRUCTURES
- Experimental analysis of the shear strength of composite concrete beams without web reinforcement
- (2020) Lisbel Rueda-García et al. ENGINEERING STRUCTURES
- Application of Neural Network Models for Mathematical Programming Problems: A State of Art Review
- (2019) Kailash Lachhwani ARCHIVES OF COMPUTATIONAL METHODS IN ENGINEERING
- Prediction of Thermal Exposure and Mechanical Behavior of Epoxy Resin Using Artificial Neural Networks and Fourier Transform Infrared Spectroscopy
- (2019) Audrius Doblies et al. Polymers
- BP neural network model for predicting the mechanical performance of a foamed wood-fiber reinforced thermoplastic starch composite
- (2019) Guang Sheng Zeng et al. POLYMER COMPOSITES
- Fabrication and modelling of the macro-mechanical properties of cross-ply laminated fibre-reinforced polymer composites using artificial neural network
- (2019) Shahzad Maqsood Khan et al. ADVANCED COMPOSITE MATERIALS
- Experimental investigations on wear and friction behaviour of SiC@r-GO reinforced Mg matrix composites produced through solvent-based powder metallurgy
- (2019) V. Kavimani et al. COMPOSITES PART B-ENGINEERING
- Properties and material models for modern construction materials at elevated temperatures
- (2019) M.Z. Naser COMPUTATIONAL MATERIALS SCIENCE
- Using convolutional neural networks to predict composite properties beyond the elastic limit
- (2019) Charles Yang et al. MRS Communications
- Prediction of Mechanical Strength of Fiber Admixed Concrete Using Multiple Regression Analysis and Artificial Neural Network
- (2019) S. Karthiyaini et al. Advances in Materials Science and Engineering
- Comparison of artificial neural network (ANN) and response surface methodology (RSM) prediction in compressive strength of recycled concrete aggregates
- (2019) Abdelkader Hammoudi et al. CONSTRUCTION AND BUILDING MATERIALS
- Understanding the basis of medical use of poly-lactide-based resorbable polymers and composites – a review of the clinical and metabolic impact
- (2019) Sergiu Vacaras et al. DRUG METABOLISM REVIEWS
- Learning image-based spatial transformations via convolutional neural networks: A review
- (2019) Nicholas J. Tustison et al. MAGNETIC RESONANCE IMAGING
- Predicting Performance of Lightweight Concrete with Granulated Expanded Glass and Ash Aggregate by Means of Using Artificial Neural Networks
- (2019) Marzena Kurpinska et al. Materials
- Artificial neural network technique to predict the properties of multiwall carbon nanotube-fly ash reinforced aluminium composite
- (2019) Udaya Devadiga et al. Journal of Materials Research and Technology-JMR&T
- SiC contents and pin temperature effect on tribological properties of Al25Zn/SiC composites
- (2019) Parmeshwar P. Ritapure et al. INTERNATIONAL JOURNAL OF REFRACTORY METALS & HARD MATERIALS
- Convolutional neural network surrogate models for the mechanical properties of periodic structures
- (2019) Mark C. Messner JOURNAL OF MECHANICAL DESIGN
- Deep neural network method for predicting the mechanical properties of composites
- (2019) Sang Ye et al. APPLIED PHYSICS LETTERS
- Prediction and optimization of mechanical properties of composites using convolutional neural networks
- (2019) Diab W. Abueidda et al. COMPOSITE STRUCTURES
- Prediction of temperature-frequency-dependent mechanical properties of composites based on thermoplastic liquid resin reinforced with carbon fibers using artificial neural networks
- (2019) Lorena Cristina Miranda Barbosa et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- A Convolutional Neural Network for Impact Detection and Characterization of Complex Composite Structures
- (2019) Iuliana Tabian et al. SENSORS
- Damage detection in steel-concrete composite bridge using vibration characteristics and artificial neural network
- (2019) Zhi Xin Tan et al. Structure and Infrastructure Engineering
- An artificial neural network supported regression model for wear rate
- (2019) Ivan I. Argatov et al. TRIBOLOGY INTERNATIONAL
- Prediction of specific wear rate for LM25/ZrO2 composites using Levenberg–Marquardt backpropagation algorithm
- (2019) Mathi Kannaiyan et al. Journal of Materials Research and Technology-JMR&T
- RSM and ANN modeling for production of Al 6351/ egg shell reinforced composite: Multi objective optimization using genetic algorithm
- (2019) Chidozie Chukwuemeka Nwobi-Okoye et al. Materials Today Communications
- Study of the fatigue behavior of composites using modular ANN with the incorporation of a posteriori failure probability
- (2019) Bruno da Cunha Diniz et al. INTERNATIONAL JOURNAL OF FATIGUE
- Properties and material models for construction materials post exposure to elevated temperatures
- (2019) M.Z. Naser et al. MECHANICS OF MATERIALS
- Artificial neural network and regression modelling to study the effect of reinforcement and deformation on volumetric wear of red mud nano particle reinforced aluminium matrix composites synthesized by stir casting
- (2018) Gampala Satyanarayana et al. BOLETIN DE LA SOCIEDAD ESPANOLA DE CERAMICA Y VIDRIO
- Artificial neural network modeling to evaluate polyvinylchloride composites’ properties
- (2018) Safwan Altarazi et al. COMPUTATIONAL MATERIALS SCIENCE
- A displacement field approach based on FEM-ANN and experiments for identification of elastic properties of composites
- (2018) Carlos Conceição António et al. INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY
- Prediction of effect of reinforcement content, flake size and flake time on the density and hardness of flake AA2024-SiC nanocomposites using neural networks
- (2018) Temel Varol et al. JOURNAL OF ALLOYS AND COMPOUNDS
- Experimental optimisation of the tribological behaviour of Al/SiC/Gr hybrid composites based on Taguchi’s method and artificial neural network
- (2018) Blaža Stojanović et al. Journal of the Brazilian Society of Mechanical Sciences and Engineering
- Optimizing the Tribological Behavior of Hybrid Copper Surface Composites Using Statistical and Machine Learning Techniques
- (2018) Titus Thankachan et al. JOURNAL OF TRIBOLOGY-TRANSACTIONS OF THE ASME
- Shear resistance prediction of concrete beams reinforced by FRP bars using artificial neural networks
- (2018) H. Naderpour et al. MEASUREMENT
- An artificial neural network-based solution to locate the multilocation faults in double circuit series capacitor compensated transmission lines
- (2018) Aleena Swetapadma et al. International Transactions on Electrical Energy Systems
- Modelling fatigue delamination growth in fibre-reinforced composites: Power-law equations or artificial neural networks?
- (2018) Giuliano Allegri MATERIALS & DESIGN
- Prediction of the Strength Properties of Carbon Fiber-Reinforced Lightweight Concrete Exposed to the High Temperature Using Artificial Neural Network and Support Vector Machine
- (2018) Harun Tanyildizi Advances in Civil Engineering
- Analysis of the Mechanical Behaviour of Asphalt Concretes Using Artificial Neural Networks
- (2018) Nicola Baldo et al. Advances in Civil Engineering
- Predicting the effect of cooling rate on the mechanical properties of glass fiber–polypropylene composites using artificial neural networks
- (2018) Mohammed S Kabbani et al. JOURNAL OF THERMOPLASTIC COMPOSITE MATERIALS
- Modeling of the mechanical and physical properties of hybrid composites produced by gas pressure infiltration
- (2018) Necat Altinkök Journal of the Brazilian Society of Mechanical Sciences and Engineering
- Evaluation of ballistic performance of hybrid Kevlar®/Cocos nucifera sheath reinforced epoxy composites
- (2018) J. Naveen et al. JOURNAL OF THE TEXTILE INSTITUTE
- Optimizing Wear Behavior of Epoxy Composites Using Response Surface Methodology and Artificial Neural Networks
- (2018) Satish Kumar D. et al. POLYMER COMPOSITES
- Applicability of Artificial Neural Networks to Predict Mechanical and Permeability Properties of Volcanic Scoria-Based Concrete
- (2018) Aref M. al-Swaidani et al. Advances in Civil Engineering
- Predicting Shear Capacity of FRP-Reinforced Concrete Beams without Stirrups by Artificial Neural Networks, Gene Expression Programming, and Regression Analysis
- (2018) Ghazi Bahroz Jumaa et al. Advances in Civil Engineering
- Structural vibration-based classification and prediction of delamination in smart composite laminates using deep learning neural network
- (2018) Asif Khan et al. COMPOSITES PART B-ENGINEERING
- A Convolutional Neural Network for Fault Classification and Diagnosis in Semiconductor Manufacturing Processes
- (2017) Ki Bum Lee et al. IEEE TRANSACTIONS ON SEMICONDUCTOR MANUFACTURING
- Optimization of hybrid aluminum composites wear using Taguchi method and artificial neural network
- (2017) Blaza Stojanovic et al. INDUSTRIAL LUBRICATION AND TRIBOLOGY
- Tribological behaviour predictions of r-GO reinforced Mg composite using ANN coupled Taguchi approach
- (2017) V. Kavimani et al. JOURNAL OF PHYSICS AND CHEMISTRY OF SOLIDS
- Multicriteria optimization of mechanical properties of aluminum composites reinforced with different reinforcing particles type
- (2017) Mostafa Akbari et al. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART E-JOURNAL OF PROCESS MECHANICAL ENGINEERING
- Predicting fatigue performance of hot mix asphalt using artificial neural networks
- (2017) Taher M. Ahmed et al. Road Materials and Pavement Design
- Parametric optimization of dry sliding wear loss of copper–MWCNT composites
- (2017) K. SOORYA PRAKASH et al. TRANSACTIONS OF NONFERROUS METALS SOCIETY OF CHINA
- Experimental investigation and prediction of wear behavior of cotton fiber polyester composites
- (2017) Hiral H. Parikh et al. Friction
- Prediction and modeling of mechanical properties in fiber reinforced self-compacting concrete using particle swarm optimization algorithm and artificial neural network
- (2016) Hadi Mashhadban et al. CONSTRUCTION AND BUILDING MATERIALS
- Polarimetric SAR Image Classification Using Deep Convolutional Neural Networks
- (2016) Yu Zhou et al. IEEE Geoscience and Remote Sensing Letters
- Chemical speciation of metals in unpolluted soils of different types: Correlation with soil characteristics and an ANN modelling approach
- (2016) J. Marković et al. JOURNAL OF GEOCHEMICAL EXPLORATION
- Regression and artificial neural network models for strength properties of engineered cementitious composites
- (2016) Khandaker M. A. Hossain et al. NEURAL COMPUTING & APPLICATIONS
- Optimization of mechanical properties of PP/EPDM/ clay nanocomposite fabricated by friction stir processing with response surface methodology and neural networks
- (2016) Mohammad Reza Nakhaei et al. POLYMER COMPOSITES
- Prediction of the shear strength of reinforced masonry walls using a large experimental database and artificial neural networks
- (2016) Víctor Aguilar et al. Structure and Infrastructure Engineering
- Optimization and Prediction of Mechanical and Thermal Properties of Graphene/LLDPE Nanocomposites by Using Artificial Neural Networks
- (2016) P. Noorunnisa Khanam et al. International Journal of Polymer Science
- Characterization, pore size measurement and wear model of a sintered Cu–W nano composite using radial basis functional neural network
- (2015) N. Leema et al. MATERIALS & DESIGN
- Deep learning in neural networks: An overview
- (2015) Jürgen Schmidhuber NEURAL NETWORKS
- Study on the sliding wear behaviour of hybrid aluminium matrix composites using Taguchi design and neural network
- (2015) Kiran Kumar Ekka et al. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART L-JOURNAL OF MATERIALS-DESIGN AND APPLICATIONS
- Prediction of tribological behaviour of rice husk ash reinforced aluminum alloy matrix composites using artificial neural network
- (2015) S. D. Saravanan et al. Russian Journal of Non-Ferrous Metals
- Application of a Neural Network Model for Prediction of Wear Properties of Ultrahigh Molecular Weight Polyethylene Composites
- (2015) Halil Ibrahim Kurt et al. International Journal of Polymer Science
- Prediction of Concrete Compressive Strength by Evolutionary Artificial Neural Networks
- (2015) Mehdi Nikoo et al. Advances in Materials Science and Engineering
- Prediction of Effect of Reinforcement Size and Volume Fraction on the Abrasive Wear Behavior of AA2014/B4Cp MMCs Using Artificial Neural Network
- (2014) Aykut Canakci et al. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING
- Fruit classification using computer vision and feedforward neural network
- (2014) Yudong Zhang et al. JOURNAL OF FOOD ENGINEERING
- Application of Artificial Neural Networks in Prediction of Diclofenac Sodium Release From Drug-Modified Zeolites Physical Mixtures and Antiedematous Activity Assessment
- (2014) Danina Krajišnik et al. JOURNAL OF PHARMACEUTICAL SCIENCES
- An Artificial Neural Network Model to Predict Material Characteristics From the Results of Miniature Disk Bending Tests
- (2014) A. K. Ghosh et al. JOURNAL OF PRESSURE VESSEL TECHNOLOGY-TRANSACTIONS OF THE ASME
- Experimental investigation and prediction of wear properties of Al/SiC metal matrix composites produced by thixomoulding method using Artificial Neural Networks
- (2014) Dursun Özyürek et al. MATERIALS & DESIGN
- Prediction of the fatigue life of natural rubber composites by artificial neural network approaches
- (2014) Ke-Lu Xiang et al. MATERIALS & DESIGN
- Experimental and Prediction of Abrasive Wear Behavior of Sintered Cu-SiC Composites Containing Graphite by Using Artificial Neural Networks
- (2014) P. Senthil Kumar et al. TRIBOLOGY TRANSACTIONS
- Artificial neural network modeling to effect of reinforcement properties on the physical and mechanical properties of Al2024–B4C composites produced by powder metallurgy
- (2013) Temel Varol et al. COMPOSITES PART B-ENGINEERING
- Application of artificial neural network in prediction of abrasion of rubber composites
- (2013) Bin Wang et al. MATERIALS & DESIGN
- Predicting modulus of rupture (MOR) and modulus of elasticity (MOE) of heat treated woods by artificial neural networks
- (2013) Sebahattin Tiryaki et al. MEASUREMENT
- Mechanical and dry sliding wear characterization of short glass fiber reinforced polyester-based homogeneous and their functionally graded composite materials
- (2013) Siddhartha et al. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART L-JOURNAL OF MATERIALS-DESIGN AND APPLICATIONS
- Prediction of thermal stability, crystallinity and thermomechanical properties of poly(ethylene oxide)/clay nanocomposites with artificial neural networks
- (2013) Engin Burgaz et al. THERMOCHIMICA ACTA
- Analysis of Sliding Wear Characteristics of BFS Filled Composites Using an Experimental Design Approach Integrated with ANN
- (2013) Prasanta Kumar Padhi et al. TRIBOLOGY TRANSACTIONS
- Artificial Neural Network Modeling of Mechanical Properties of Calcium Carbonate Impregnated Coir-Polyester Composites
- (2013) S. Jayabal et al. TRANSACTIONS OF THE INDIAN INSTITUTE OF METALS
- Artificial Neural Network prediction of Cu–Al2O3 composite properties prepared by powder metallurgy method
- (2013) Mostafa Amirjan et al. Journal of Materials Research and Technology-JMR&T
- Strength enhancement modeling of concrete cylinders confined with CFRP composites using artificial neural networks
- (2012) Mostafa Jalal et al. COMPOSITES PART B-ENGINEERING
- Predicting the mechanical properties of glass fiber reinforced polymers via artificial neural network and adaptive neuro-fuzzy inference system
- (2012) H. Fazilat et al. COMPUTATIONAL MATERIALS SCIENCE
- Automated text classification using a dynamic artificial neural network model
- (2012) M. Ghiassi et al. EXPERT SYSTEMS WITH APPLICATIONS
- Comparative study between the PNL method and a MN in modelling fatigue of composite materials
- (2012) A. SILVA BELÍSIO et al. FATIGUE & FRACTURE OF ENGINEERING MATERIALS & STRUCTURES
- Experimental study and prediction using ANN on mass loss of hybrid composites
- (2012) C. Velmurugan et al. INDUSTRIAL LUBRICATION AND TRIBOLOGY
- Prediction of mechanical properties of compatibilized styrene/natural-rubber blend by using reaction conditions: Central composite design vs. artificial neural networks
- (2012) Natsupa Sresungsuwan et al. JOURNAL OF APPLIED POLYMER SCIENCE
- Criteria for the use of modular networks: fatigue in composite materials
- (2012) Bremmer Bernardo Vasconcelos de Sena et al. JOURNAL OF COMPOSITE MATERIALS
- Using slippage theory to analyze shear behavior of loop-formed fiber reinforced soil composites
- (2012) Sayyed Mahdi Hejazi et al. Journal of Industrial Textiles
- Experimental and prediction of sintered Cu–W composite by using artificial neural networks
- (2012) S.C. Vettivel et al. MATERIALS & DESIGN
- Modeling the influence of a process control agent on the properties of metal matrix composite powders using artificial neural networks
- (2012) Aykut Canakci et al. POWDER TECHNOLOGY
- Multi-criteria decision making development of ion chromatographic method for determination of inorganic anions in oilfield waters based on artificial neural networks retention model
- (2011) Štefica Cerjan Stefanović et al. ANALYTICA CHIMICA ACTA
- Prediction of strength of reinforced lightweight soil using an artificial neural network
- (2011) H.I. Park et al. ENGINEERING COMPUTATIONS
- Artificial neural network prediction of the wear rate of powder metallurgy Al/Al2O3 metal matrix composites
- (2011) T S Mahmoud PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART L-JOURNAL OF MATERIALS-DESIGN AND APPLICATIONS
- Prediction of wear properties in A356 matrix composite reinforced with B4C particulates
- (2011) Mohsen Ostad Shabani et al. SYNTHETIC METALS
- Artificial neural networks for predicting sliding friction and wear properties of polyphenylene sulfide composites
- (2011) Lada A. Gyurova et al. TRIBOLOGY INTERNATIONAL
- Using Artificial Neural Networks to Predict the Fatigue Life of Different Composite Materials Including the Stress Ratio Effect
- (2010) Mohamed Al-Assadi et al. APPLIED COMPOSITE MATERIALS
- Evaluation and prediction of wear response of pine wood dust filled epoxy composites using neural computation
- (2010) Ganguluri Kranthi et al. COMPUTATIONAL MATERIALS SCIENCE
- Prediction of mechanical properties of waste polypropylene/waste ground rubber tire powder blends using artificial neural networks
- (2010) Shu Ling Zhang et al. MATERIALS & DESIGN
- Artificial Neural Network Approach to Predict Compressive Strength of Concrete through Ultrasonic Pulse Velocity
- (2010) M. Bilgehan et al. RESEARCH IN NONDESTRUCTIVE EVALUATION
- Prediction of friction coefficient of treated betelnut fibre reinforced polyester (T-BFRP) composite using artificial neural networks
- (2010) Umar Nirmal TRIBOLOGY INTERNATIONAL
- Neural network modeling and analysis of gel casting preparation of porous Si3N4 ceramics
- (2009) Juanli Yu et al. CERAMICS INTERNATIONAL
- Prediction of wear behaviors of nickel free stainless steel–hydroxyapatite bio-composites using artificial neural network
- (2009) M. Younesi et al. COMPUTATIONAL MATERIALS SCIENCE
- A proposed framework for control chart pattern recognition in multivariate process using artificial neural networks
- (2009) T.T. El-Midany et al. EXPERT SYSTEMS WITH APPLICATIONS
- A Novel Connectionist System for Unconstrained Handwriting Recognition
- (2009) A. Graves et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Prediction of Bearing Strength of Two Serial Pinned/Bolted Composite Joints using Artificial Neural Networks
- (2009) Faruk Sen et al. JOURNAL OF COMPOSITE MATERIALS
- A Comparative Study of Statistical Outlier Analysis and ANN Methods for Damage Detection and Assessment in Composite Structures
- (2009) Ajay Kesavan et al. JOURNAL OF INTELLIGENT MATERIAL SYSTEMS AND STRUCTURES
- Erosion Studies of Short Glass Fiber-reinforced Thermoplastic Composites and Prediction of Erosion Rate Using ANNs
- (2009) Arjula Suresh et al. JOURNAL OF REINFORCED PLASTICS AND COMPOSITES
- Study on mechanical and erosion wear behavior of hybrid composites using Taguchi experimental design
- (2009) S.S. Mahapatra et al. MATERIALS & DESIGN
- Prediction of mechanical properties of polypropylene/waste ground rubber tire powder treated by bitumen composites via uniform design and artificial neural networks
- (2009) Shu Ling Zhang et al. MATERIALS & DESIGN
- An artificial neural network for prediction of the friction coefficient of multi-layer polymeric composites in three different orientations
- (2009) T Nasir et al. PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART C-JOURNAL OF MECHANICAL ENGINEERING SCIENCE
- Modeling the sliding wear and friction properties of polyphenylene sulfide composites using artificial neural networks
- (2009) Lada A. Gyurova et al. WEAR
- Modelling cutting power and tool wear in turning of aluminium matrix composites using Artificial Neural Networks
- (2008) Liujie Xu et al. INTERNATIONAL JOURNAL OF MATERIALS & PRODUCT TECHNOLOGY
- Prediction of tribological behavior of aluminum–copper based composite using artificial neural network
- (2008) Mohammed Hayajneh et al. JOURNAL OF ALLOYS AND COMPOUNDS
- Characterization of Failure Modes in CFRP Composites — An ANN Approach
- (2008) Chandrashekhar Bhat et al. JOURNAL OF COMPOSITE MATERIALS
- Prediction on tribological properties of carbon fiber and TiO2 synergistic reinforced polytetrafluoroethylene composites with artificial neural networks
- (2008) Jiahua Zhu et al. MATERIALS & DESIGN
- Prediction of wear behaviour of A356/SiCp MMCs using neural networks
- (2008) F.S. Rashed et al. TRIBOLOGY INTERNATIONAL
- Study on friction and wear behavior of polyphenylene sulfide composites reinforced by short carbon fibers and sub-micro TiO2 particles
- (2007) Zhenyu Jiang et al. COMPOSITES SCIENCE AND TECHNOLOGY
- Neural network based prediction on mechanical and wear properties of short fibers reinforced polyamide composites
- (2007) Zhenyu Jiang et al. MATERIALS & DESIGN
Find the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
SearchAdd your recorded webinar
Do you already have a recorded webinar? Grow your audience and get more views by easily listing your recording on Peeref.
Upload Now