| People | Locations | Statistics |
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| Naji, M. |
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| Motta, Antonella |
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| Aletan, Dirar |
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| Mohamed, Tarek |
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| Ertürk, Emre |
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| Taccardi, Nicola |
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| Kononenko, Denys |
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| Petrov, R. H. | Madrid |
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| Alshaaer, Mazen | Brussels |
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| Bih, L. |
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| Casati, R. |
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| Muller, Hermance |
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| Kočí, Jan | Prague |
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| Šuljagić, Marija |
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| Kalteremidou, Kalliopi-Artemi | Brussels |
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| Azam, Siraj |
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| Ospanova, Alyiya |
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| Blanpain, Bart |
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| Ali, M. A. |
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| Popa, V. |
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| Rančić, M. |
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| Ollier, Nadège |
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| Azevedo, Nuno Monteiro |
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| Landes, Michael |
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| Rignanese, Gian-Marco |
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Asadnia, Mohsen
in Cooperation with on an Cooperation-Score of 37%
Topics
Publications (31/31 displayed)
- 2024Transient piezoresistive strain sensors based on elastic biopolymer thin filmscitations
- 2023Highly stretchable strain sensors based on gold thin film reinforced with carbon nanofiberscitations
- 2023A review on wearable electrospun polymeric piezoelectric sensors and energy harvesterscitations
- 2023Natural clay membranescitations
- 2023Superhydrophobic Al2O3/MMT-PDMS coated fabric for self-cleaning and oil-water separation applicationcitations
- 2022Carbon nanofiber-reinforced Pt thin film-based airflow sensor for respiratory monitoringcitations
- 2022Steering of beam using cylindrical arrangements in a metallic parallel plates structure operating over Ku-bandcitations
- 2022Biomimetic ultraflexible piezoresistive flow sensor based on graphene nanosheets and PVA hydrogelcitations
- 2022Biomimetic ultraflexible piezoresistive flow sensor based on graphene nanosheets and PVA hydrogelcitations
- 2022Miniaturized wideband antenna prototype operating over the Ku-bandcitations
- 2022Fabrication of tubular ceramic membranes as low-cost adsorbent using natural clay for heavy metals removalcitations
- 2022Highly stable Li+ selective electrode with metal-organic framework as ion-to-electron transducercitations
- 2022Realization of three dimensional printed multi layer wide band prototypecitations
- 2021Polymeric piezoresistive airflow sensor to monitor respiratory patternscitations
- 2021Polymeric piezoresistive airflow sensor to monitor respiratory patterns
- 2021Mechanobiology of dental pulp stem cells at the interface of aqueous-based fabricated ZIF8 thin filmcitations
- 2021Development of Ultrasensitive Biomimetic Auditory Hair Cells Based on Piezoresistive Hydrogel Nanocompositescitations
- 2021Development of ultrasensitive biomimetic auditory hair cells based on piezoresistive hydrogel nanocompositescitations
- 2020Bienzymatic modification of polymeric membranes to mitigate biofoulingcitations
- 20203D printing of inertial microfluidic devicescitations
- 2020Surface modification of polypropylene membrane for the removal of iodine using polydopamine chemistrycitations
- 2019A stripline-based planar wideband feed for high-gain antennas with partially reflecting superstructurecitations
- 2019A Stripline-Based Planar Wideband Feed for High-Gain Antennas with Partially Reflecting Superstructurecitations
- 2018Mass transfer and flow in additive manufacturing of a spherical componentcitations
- 2017Cupula-inspired hyaluronic acid-based hydrogel encapsulation to form biomimetic MEMS flow sensorscitations
- 2016From Biological Cilia to Artificial Flow Sensorscitations
- 2016Superlattice Barrier HgCdTe nBn Infrared Photodetectorscitations
- 2013Modeling of TiC-N Thin Film Coating Process on Drills Using Particle Swarm Optimization Algorithmcitations
- 2011The selection of milling parameters by the PSO-based neural network modeling methodcitations
- 2011Modelling of the thrust force of the drilling operation on PA6-nanoclay nanocomposites using particle swarm optimizationcitations
- 2010Using particle swarm optimization based neural network for modeling of thrust force drilling of PA-6/ Nanoclay Nanocompositescitations
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article
Using particle swarm optimization based neural network for modeling of thrust force drilling of PA-6/ Nanoclay Nanocomposites
Abstract
<p>This paper presents a newly approach for modeling thrust force in drilling of PA-6/ Nanoclay Nanocomposites materials, by using Particle Swarm Optimization based Neural Network (PSONN). In this regard, advantages of statistical experimental algorithm technique, experimental measurements, particle swarm optimization and artificial neural network are exploited in an integrated manner. For this purpose, numerous experiments for PA-6 and PA-6/ Nanoclay Nanocomposites are conducted to obtain thrust force values by using drill of high speed steel with 118° point angles and 2mm in diameter. Then, a predictive model for thrust force is created by using PSONN algorithm. Also, the training capacity of PSONN is compared to that of the conventional neural network. The results indicate that nanoclay content on PA-6 polyamide significantly decrease the thrust force. Also, the obtained results for modeling of thrust force have shown very good training capacity of the proposed PSONN algorithm with compared to that of a conventional neural network (BPNN).</p>