Study on Fuzzy Soil Balanced Fertilization Model System Based on Neural Network

2021 ◽  
pp. 1581-1585
Author(s):  
Zheqing Tang ◽  
Shan Ning ◽  
Xiqiang Sun ◽  
Qiuduo Zhao
Keyword(s):  
Neural Network ◽  
Model System ◽  
Balanced Fertilization

Predicting delays in prefabricated projects: SD-BP neural network to define effects of risk disruption

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Ying Zhao ◽  
Wei Chen ◽  
Mehrdad Arashpour ◽  
Zhuzhang Yang ◽  
Chengxin Shao ◽  
...  
Keyword(s):  
Neural Network ◽  
Prediction Model ◽  
Bp Neural Network ◽  
Input Parameter ◽  
Model System ◽  
Extreme Condition ◽  
Content Type ◽  
Schedule Delay ◽  
Wide Range ◽  
Delay Prediction

PurposePrefabricated construction is often hindered by scheduling delays. This paper aims to propose a schedule delay prediction model system, which can provide the key information for controlling the delay effects of risk-related factors on scheduling in prefabricated construction.Design/methodology/approachThis paper combines SD (System Dynamics) and BP (Back Propagation) neural network to predict risk related delays. The SD-based prediction model focuses on dynamically presenting the interrelated impacts of risk events and activities along with workflow. While BP neural network model is proposed to evaluate the delay effect for a single risk event disrupting a single job, which is the necessary input parameter of SD-based model.FindingsThe established model system is validated through a structural test, an extreme condition test, a sensitivity test, and an error test, and shows an excellent performance on aspect of reliability and accuracy. Furthermore, 5 scenarios of case application during 3 different projects located in separate cities prove the prediction model system can be applied in a wide range.Originality/valueThis paper contributes to academic research on combination of SD and BP neural network at the operational level prediction, and a practical prediction tool supporting managers to take decision-making in a timely manner against delays.

Tadpole Swimming Network

2017 ◽  
pp. 545-552
Author(s):  
Keith T. Sillar ◽  
Wen-Chang Li
Keyword(s):  
Neural Network ◽  
Locomotor Activity ◽  
Simple Model ◽  
Motor Program ◽  
Model System ◽  
Detailed Knowledge ◽  
Sensory Adaptation ◽  
Simple Model System ◽  
Network Output ◽  
Network Operation

Xenopus laevis frog tadpoles near the time of hatching have proved to be an excellent model system in which to explore the neural mechanisms responsible for the initiation, maintenance, sensory adaptation, and termination of rhythmic locomotor activity in vertebrates. The underlying neural network is one of the most completely understood in any vertebrate. Detailed knowledge has accrued over the last 40 years, highlighting conserved operational features of vertebrate rhythm generators and serving as an invaluable platform from which to investigate associated issues of fundamental importance in neuroscience, such as motor program switching, transmitter corelease, network development, neuromodulation, and metamodulation of network operation. There are many advantages of this simple model system, including the presence of a well-defined network output that relates directly to the behavior of the animal under study (namely, swimming locomotion).

scholarly journals SISTEM PERINGKAS OTOMATIS ABSTRAKTIF DENGAN MENGGUNAKAN RECURRENT NEURAL NETWORK

2018 ◽  
Vol 2 (1) ◽  
pp. 65 ◽  
Author(s):  
Kuncoro Yoko ◽  
Viny Christanti Mawardi ◽  
Janson Hendryli
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Model System ◽  
Text Summarization ◽  
Word Embedding ◽  
System Evaluation ◽  
Data Set ◽  
Hidden States ◽  
Bahasa Indonesia

Abstractive Text Summarization try to creates a shorter version of a text while preserve its meaning. We try to use Recurrent Neural Network (RNN) to create summaries of Bahasa Indonesia text. We get corpus from Detik dan Kompas site news. We used word2vec to create word embedding from our corpus then train our data set with RNN to create a model. This model used to generate news. We search the best model by changing word2vec size and RNN hidden states. We use system evaluation and Q&A Evaluation to evaluate our model. System evaluation showed that model with 6457 data set, 200 word2vec size, and 256 RNN hidden states gives best accuracy for 99.8810%. This model evaluated by Q&A Evaluation. Q&A Evaluation showed that the model gives 46.65% accurary.

scholarly journals Deep neural network based histological scoring of lung fibrosis and inflammation in the mouse model system

PLoS ONE ◽  
2018 ◽  
Vol 13 (8) ◽  
pp. e0202708 ◽  
Author(s):  
Fabian Heinemann ◽  
Gerald Birk ◽  
Tanja Schoenberger ◽  
Birgit Stierstorfer
Keyword(s):  
Neural Network ◽  
Mouse Model ◽  
Lung Fibrosis ◽  
Deep Neural Network ◽  
Model System ◽  
Mouse Model System

Intelligent Optimization of Material Mixing Ratio and Process Parameters for Aerated Concrete

2011 ◽  
Vol 243-249 ◽  
pp. 7026-7035
Author(s):  
Fang Yang ◽  
Lin Zhu Sun ◽  
Zi Ling Xie ◽  
Ya Gang Zhou
Keyword(s):  
Neural Network ◽  
Process Parameters ◽  
Reference Value ◽  
Model System ◽  
Process Equipment ◽  
Mixing Ratio ◽  
Sample Test ◽  
Aerated Concrete ◽  
Optimal Material ◽  
Material Mixing

To determine the optimal material mixing ratio of and process parameters for aerated concrete products, we adopted various combinations of material mixing ratio and process parameters to test aerated concrete according to the characteristics of local material and process equipment in this study, and obtained the strength and density of the aerated concrete. Using artificial neural network, we built a three-layer neural network model, which was trained based on the data of test samples to obtain a neural network based model system. Sample test showed that the predicted values of the model system fit the test values well; we utilized this system to analyze the material mixing ratio of and process parameters for aerated concrete products, and obtained their optimization results. The strength and density of the aerated concrete manufactured with the optimized parameters reached the desired targets. This method has some reference value for instructing the production of aerated concrete.

Forecast of Blasting Fragmentation Distribution Based on BP Neural Network

2012 ◽  
Vol 619 ◽  
pp. 3-8 ◽  
Author(s):  
Hong Gao ◽  
Zhi Liang Fu
Keyword(s):  
Neural Network ◽  
Network Model ◽  
Neural Network Model ◽  
Bp Neural Network ◽  
Industrial Production ◽  
Influence Factors ◽  
Model System ◽  
Rock Blasting ◽  
Bp Neural Network Model ◽  
Main Influence

The influence factors of rock blasting fragmentation distribution are analyzed, 10 main influence factors are selected from these. Using the MATLAB BP neural network model system to analyze blasting fragmentation distribution of +860 level face at Yi Chun tantalum-niobium mine, successfully predicted the blasting fragmentation distribution, it is favorable to design the blasting parameters and industrial production.

A Protozoan Model for Golgi-Associated Calcification

1971 ◽  
Vol 29 ◽  
pp. 332-333
Author(s):  
D. C. Williams ◽  
D. E. Outka
Keyword(s):  
Golgi Apparatus ◽  
Organic Matrix ◽  
Model System ◽  
Sequential Formation

Many studies have shown that the Golgi apparatus is involved in a variety of synthetic activities, and probably no Golgi product is more elaborate than the scales produced by various kinds of phytoflagellates. The formation of calcified scales (coccoliths, Fig. 1,2) of the coccolithophorid phytoflagellates provides a particularly interesting model system for the study of biological mineralization, and the sequential formation of Golgi products.The coccoliths of Hymenomonas carterae consist of a scale-like base (Fig. 2 and 4, b) with a highly structured calcified (CaCO3) rim composed of two distinct elements which alternate about the base periphery (Fig. 1 and 3, A, B). Each element is enveloped by a sheath-like organic matrix (Fig. 3; Fig. 4, m).

Existence of DNA in yeast microbodies

1978 ◽  
Vol 36 (2) ◽  
pp. 232-233
Author(s):  
Masako Osumi ◽  
Misuzu Nagano ◽  
Hiroko Kazama
Keyword(s):  
Catalase Activity ◽  
Buoyant Density ◽  
Model System ◽  
Contour Length ◽  
Native State ◽  
Normal Alkane ◽  
Remarkable Increase ◽  
Dna Molecule ◽  
Mitochondrial Dnas

We have found that microbodies appeared profusely together with a remarkable increase in catalase activity in normal alkane-grown cells of hydrocarbon-utilizing Candida yeasts, and that the microbodies multiplied by division in these cells. These features of Candida yeasts seem to provide a useful model system for studies on the biogenesis of the microbody. Subsequently, we have succeeded in isolation of Candida microbodies in an apparently native state, as judged biochemically and morphologically. The presence of DNA in the purified microbody fraction thus obtained was proved by the diphenylamine method. DNA molecule of about 15 urn in contour length was released from an isolated microbody. The physicochemical analyses of the microbody DNA revealed that its buoyant density differed from nuclear and mitochondrial DNAs. All these results lead us to the possibility that there is a novel type of DNA in microbodies.

The coprecipitation of Cr3P and Cr in Cu

1988 ◽  
Vol 46 ◽  
pp. 764-765
Author(s):  
M.J. Witcomb ◽  
U. Dahmen ◽  
K.H. Westmacott
Keyword(s):  
Orientation Relationship ◽  
Interface Structure ◽  
Model System ◽  
Relative Orientation ◽  
Age Hardening ◽  
Precipitation Behavior ◽  
Solution Treated ◽  
Small Needle ◽  
Diffraction Patterns ◽  
Interface Structures

Cu-Cr age-hardening alloys are of interest as a model system for the investigation of fcc/bcc interface structures. Several past studies have investigated the morphology and interface structure of Cr precipitates in a Cu matrix (1-3) and good success has been achieved in understanding the crystallography and strain contrast of small needle-shaped precipitates. The present study investigates the effect of small amounts of phosphorous on the precipitation behavior of Cu-Cr alloys.The same Cu-0.3% Cr alloy as was used in earlier work was rolled to a thickness of 150 μm, solution treated in vacuum at 1050°C for 1h followed by quenching and annealing for various times at 820 and 863°C.Two laths and their corresponding diffraction patterns in an alloy aged 2h at 820°C are shown in correct relative orientation in Fig. 1. To within the limit of accuracy of the diffraction patterns the orientation relationship was that of Kurdjumov-Sachs (KS), i.e. parallel close-packed planes and directions.

Membrane-associated microtubular areays induced in proximal myelinated processes of dorsal root ganglia by large doses of vitamin B6

1986 ◽  
Vol 44 ◽  
pp. 368-369
Author(s):  
V.J. Montpetit ◽  
S. Dancea ◽  
L. Tryphonas ◽  
D.F. Clapin
Keyword(s):  
Animal Model ◽  
Endoplasmic Reticulum ◽  
Dorsal Root Ganglia ◽  
Rough Endoplasmic Reticulum ◽  
Dorsal Root ◽  
Vitamin B6 ◽  
Morphological Changes ◽  
Model System ◽  
Sensory Nerves ◽  
Peripheral Sensory

Very large doses of pyridoxine (vitamin B6) are neurotoxic in humans, selectively affecting the peripheral sensory nerves. We have undertaken a study of the morphological and biochemical aspects of pyridoxine neurotoxicity in an animal model system. Early morphological changes in dorsal root ganglia (DRG) associated with pyridoxine megadoses include proliferation of neurofilaments, ribosomes, rough endoplasmic reticulum, and Golgi complexes. We present in this report evidence of the formation of unique aggregates of microtubules and membranes in the proximal processes of DRG which are induced by high levels of pyridoxine.

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