Overview of Cellular Computing-Basic Principles and Applications

2016 ◽  
pp. 637-662
Author(s):  
Amit Das ◽  
Rakhi Dasgupta ◽  
Angshuman Bagchi
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Life Sciences ◽  
Science Research ◽  
The Other ◽  
Computational Algorithms ◽  
Basic Principles ◽  
Computing Power ◽  
Cellular Computing ◽  
The Impact

Computers, due to their raw speed and massive computing power, have been highly used by biologists to expedite life science research whereas several computational algorithms like artificial neural network, genetic algorithm and many similar ones have been inspired by the behaviors of several biological or cellular entities. However till date both these disciplines i.e. life sciences and computer sciences have mostly progressed separately while recent studies are increasingly highlighting the impact of each discipline on the other. The chapter describes several features of biological systems which could be used for further optimizations of computer programs or could be engineered to harness necessary computational capabilities in lieu of traditional silico chip systems. We also highlight underlying challenges and avenues of implementations of cellular computing.

Overview of Cellular Computing-Basic Principles and Applications

2020 ◽  
pp. 1895-1920
Author(s):  
Amit Das ◽  
Rakhi Dasgupta ◽  
Angshuman Bagchi
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Life Sciences ◽  
Science Research ◽  
The Other ◽  
Computational Algorithms ◽  
Basic Principles ◽  
Computing Power ◽  
Cellular Computing ◽  
The Impact

Computers, due to their raw speed and massive computing power, have been highly used by biologists to expedite life science research whereas several computational algorithms like artificial neural network, genetic algorithm and many similar ones have been inspired by the behaviors of several biological or cellular entities. However till date both these disciplines i.e. life sciences and computer sciences have mostly progressed separately while recent studies are increasingly highlighting the impact of each discipline on the other. The chapter describes several features of biological systems which could be used for further optimizations of computer programs or could be engineered to harness necessary computational capabilities in lieu of traditional silico chip systems. We also highlight underlying challenges and avenues of implementations of cellular computing.

Hangzhou Housing Demand Forecasting Model Based on BP Neural Network of Genetic Algorithm Optimization

2014 ◽  
Vol 587-589 ◽  
pp. 37-41 ◽  
Author(s):  
Yi Hua Mao ◽  
Meng Bo Zhang ◽  
Ning Bo Yao
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Real Estate ◽  
Housing Market ◽  
Bp Neural Network ◽  
Housing Demand ◽  
Forecasting Model ◽  
Algorithm Optimization ◽  
Genetic Algorithm Optimization ◽  
The Impact

Hangzhou, the capital of Zhejiang province and a famous scenic tourist city in China, goes at the forefront of the country for its high real estate prices, which hold a very important position of orientation to pricing in the real estate markets of the Yangtze River Delta region and of the whole country as well. The price trend of Hangzhou's real estate is even related to the sustainable development of the city. This paper uses the macro data on the housing market in Hangzhou during 1999-2012 to establish a forecasting model which is based on BP neural network of genetic algorithm optimization. With MATLAB software exploited for programming and simulation, the prediction made by the model about the housing demand in Hangzhou and the subsequent re-examination show that the model has high precision. But due to the impact of the national macro-control policies on housing market, the predictive value of some years may fluctuate to a certain extent.

Energy Demand Forecast of City Based on Cellular Genetic Algorithm

2012 ◽  
Vol 263-266 ◽  
pp. 2122-2125
Author(s):  
Yu Gui Cheng
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Bp Neural Network ◽  
Energy Demand ◽  
The Other ◽  
Demand Forecast ◽  
Minimum Error ◽  
Search Optimization ◽  
Cellular Genetic Algorithm ◽  
Better Than

As a branch of genetic algorithm (GA), cellular genetic algorithm (CGA) has been used in search optimization of the population in recent years. Compared with traditional genetic algorithm and the algorithm combined with traditional genetic algorithm and BP neural network, energy demand forecast of city by the method of combining cellular genetic algorithm and BP neural network had the characteristic of the minimum training times, the shortest consumption time and the minimum error. Meanwhile, it was better than the other two algorithms from the point of fitting effect.

The use of genetic algorithm and self-updating artificial neural network for the inverse design of cabin environment

2016 ◽  
Vol 26 (3) ◽  
pp. 347-354 ◽  
Author(s):  
Tian-hu Zhang ◽  
Xue-yi You
Keyword(s):  
Neural Network ◽  
Fluid Dynamics ◽  
Genetic Algorithm ◽  
Computational Fluid Dynamics ◽  
Artificial Neural Network ◽  
Computational Cost ◽  
The Self ◽  
Inverse Design ◽  
Artificial Neural ◽  
The Impact

The inverse process of computational fluid dynamics was used to explore the expected indoor environment with the preset objectives. An inverse design method integrating genetic algorithm and self-updating artificial neural network is presented. To reduce the computational cost and eliminate the impact of prediction error of artificial neural network, a self-updating artificial neural network is proposed to realize the self-adaption of computational fluid dynamics database, where all the design objectives of solutions are obtained by computational fluid dynamics instead of artificial neural network. The proposed method was applied to the inverse design of an MD-82 aircraft cabin. The result shows that the performance of artificial neural network is improved with the increase of computational fluid dynamics database. When the number of computational fluid dynamics cases is more than 80, the success rate of artificial neural network increases to more than 40%. Comparing to genetic algorithm and computational fluid dynamics, the proposed hybrid method reduces about 53% of the computational cost. The pseudo solutions are avoided when the self-updating artificial neural network is adopted. In addition, the number of computational fluid dynamics cases is determined automatically, and the requirement of human adjustment is avoided.

The Impact of Physically Attractive Models on Advertising Evaluations

1977 ◽  
Vol 14 (4) ◽  
pp. 538-555 ◽  
Author(s):  
Michael J. Baker ◽  
Gilbert A. Churchill
Keyword(s):  
Social Science ◽  
Physical Attractiveness ◽  
Social Science Research ◽  
Science Research ◽  
The Other ◽  
Male And Female ◽  
Initial Perception ◽  
The Impact ◽  
Physically Attractive ◽  
People’S Perceptions

A considerable amount of social science research suggests an individual's initial perception of and reaction to another individual are affected by the physical attractiveness of the other person. The authors attempt to assess whether this general finding applies to people's perceptions of advertisements. Specifically, they assess the impact of attractiveness of male and female models on subjects’ evaluations of ads, and seek to determine whether the reactions depend on the sex of the ad reader or on the type of product being advertised.

scholarly journals Business English Translation Model Based on BP Neural Network Optimized by Genetic Algorithm

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yanning Chen
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Bp Neural Network ◽  
English Translation ◽  
Bp Algorithm ◽  
Business English ◽  
Translation Model ◽  
Semantic Errors ◽  
Purpose Of Business ◽  
The Impact

In recent years, most of the communication places are using business English manual simultaneous interpretation or electronic equipment translation. In the context of diverse cultures, the way English is used and its grammar vary from country to country. In the face of this situation, how to optimize business English translation technology and improve the accuracy of business communication content is one of the research contents of scholars all over the world. This paper first introduces the purpose of business English translation and the gap between business English translation and general English translation. Secondly, a genetic algorithm is used to optimize the structure of the BP neural network, and the combination of the two improves the ability of translation search. This paper compares the influence of the traditional BP algorithm and the BP algorithm optimized by genetic algorithm on the construction of a business English translation model. The results show that BP neural network optimized by the genetic algorithm can improve the speed of business English text translation, reduce the impact of semantic errors on the accuracy of the translation model, and improve the efficiency of translation.

scholarly journals Solder Joint Reliability Risk Estimation by AI-Assisted Simulation Framework with Genetic Algorithm to Optimize the Initial Parameters for AI Models

Materials ◽  
2021 ◽  
Vol 14 (17) ◽  
pp. 4835
Author(s):  
Cadmus Yuan ◽  
Xuejun Fan ◽  
Gouqi Zhang
Keyword(s):  
Neural Network ◽  
Genetic Algorithm ◽  
Solder Joint ◽  
Risk Estimation ◽  
Time Dependent ◽  
Simulation Framework ◽  
Solder Joint Reliability ◽  
Joint Reliability ◽  
Solder Joint Fatigue ◽  
The Impact

Solder joint fatigue is one of the critical failure modes in ball-grid array packaging. Because the reliability test is time-consuming and geometrical/material nonlinearities are required for the physics-driven model, the AI-assisted simulation framework is developed to establish the risk estimation capability against the design and process parameters. Due to the time-dependent and nonlinear characteristics of the solder joint fatigue failure, this research follows the AI-assisted simulation framework and builds the non-sequential artificial neural network (ANN) and sequential recurrent neural network (RNN) architectures. Both are investigated to understand their capability of abstracting the time-dependent solder joint fatigue knowledge from the dataset. Moreover, this research applies the genetic algorithm (GA) optimization to decrease the influence of the initial guessings, including the weightings and bias of the neural network architectures. In this research, two GA optimizers are developed, including the “back-to-original” and “progressing” ones. Moreover, we apply the principal component analysis (PCA) to the GA optimization results to obtain the PCA gene. The prediction error of all neural network models is within 0.15% under GA optimized PCA gene. There is no clear statistical evidence that RNN is better than ANN in the wafer level chip-scaled packaging (WLCSP) solder joint reliability risk estimation when the GA optimizer is applied to minimize the impact of the initial AI model. Hence, a stable optimization with a broad design domain can be realized by an ANN model with a faster training speed than RNN, even though solder fatigue is a time-dependent mechanical behavior.

Research on behavior recognition based on feature fusion of automatic coder and recurrent neural network

2020 ◽  
Vol 39 (6) ◽  
pp. 8927-8935
Author(s):  
Bing Zheng ◽  
Dawei Yun ◽  
Yan Liang
Keyword(s):  
Neural Network ◽  
Recurrent Neural Network ◽  
Behavior Pattern ◽  
Rapid Development ◽  
Video Data ◽  
Support Vector ◽  
Behavior Recognition ◽  
Learning Methods ◽  
The Impact ◽  
Internet Of Things Technology

Under the impact of COVID-19, research on behavior recognition are highly needed. In this paper, we combine the algorithm of self-adaptive coder and recurrent neural network to realize the research of behavior pattern recognition. At present, most of the research of human behavior recognition is focused on the video data, which is based on the video number. At the same time, due to the complexity of video image data, it is easy to violate personal privacy. With the rapid development of Internet of things technology, it has attracted the attention of a large number of experts and scholars. Researchers have tried to use many machine learning methods, such as random forest, support vector machine and other shallow learning methods, which perform well in the laboratory environment, but there is still a long way to go from practical application. In this paper, a recursive neural network algorithm based on long and short term memory (LSTM) is proposed to realize the recognition of behavior patterns, so as to improve the accuracy of human activity behavior recognition.

Modernism, Empiricism, and Rationalism

2016 ◽  
Vol 46 (1) ◽  
pp. 38-47
Author(s):  
Geoffrey Squires
Keyword(s):  
Twentieth Century ◽  
The Other ◽  
Modern Poetry ◽  
Philosophical Perspective ◽  
Irish Poetry ◽  
Dimensional Spectrum ◽  
Culture History ◽  
The World ◽  
The Impact ◽  
Rule Out

Modernism is usually defined historically as the composite movement at the beginning of the twentieth century which led to a radical break with what had gone before in literature and the other arts. Given the problems of the continuing use of the concept to cover subsequent writing, this essay proposes an alternative, philosophical perspective which explores the impact of rationalism (what we bring to the world) on the prevailing empiricism (what we take from the world) of modern poetry, which leads to a concern with consciousness rather than experience. This in turn involves a re-conceptualisation of the lyric or narrative I, of language itself as a phenomenon, and of other poetic themes such as nature, culture, history, and art. Against the background of the dominant empiricism of modern Irish poetry as presented in Crotty's anthology, the essay explores these ideas in terms of a small number of poets who may be considered modernist in various ways. This does not rule out modernist elements in some other poets and the initial distinction between a poetics of experience and one of consciousness is better seen as a multi-dimensional spectrum that requires further, more detailed analysis than is possible here.

Sign in / Sign up

Export Citation Format

Share Document