The Improved Antlion Optimizer and Artificial Neural Network for Chinese Influenza Prediction

Hu, Hongping; Li, Yangyang; Bai, Yanping; Zhang, Juping; Liu, Maoxing

doi:10.1155/2019/1480392

Cited by 23 publications

(11 citation statements)

References 39 publications

(43 reference statements)

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“…Nature-inspired algorithm simulates hunting Ant Lion and getting food. This algorithm was first suggested by Mirjalili in 2015 to solve optimization problems [12,13].…”

Section: Ant Lion Algorithm (Alo)mentioning

confidence: 99%

A Novel Approach to Spoken Arabic Number Recognition Based on Developed Ant Lion Algorithm

Ramo¹,

Younis²

2021

IJC

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Intelligent spoken system is constructed to recognize numbers spoken in Arabic language by different people. Series of operations are performed on audio sound file as pre-processing stages. A novel approach is applied to extract features of audio files called Max Mean Log to reduce audio file dimensions in an efficient manner. Several stages of initial processing are used to prepare the file for the next step of the recognition process. The recognition process begins with the use of Antlion’s advanced intelligence algorithm to determine the type of the spoken number in Arabic and later convert it to a visual text that represents the value of the spoken number. The current proposal method is relatively fast and very effective. The percentage of recognizing numbers spoken by the proposed algorithm is 99%. For 1,800 different audio files, the error rate was 1%. Additional 40 audio files were used that are different from people’s original dataset. Due to an additional examination of the system and its ability to recognize the audio file, the rate of discrimination for such files was 72.5%.

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“…Nature-inspired algorithm simulates hunting Ant Lion and getting food. This algorithm was first suggested by Mirjalili in 2015 to solve optimization problems [12,13].…”

Section: Ant Lion Algorithm (Alo)mentioning

confidence: 99%

A Novel Approach to Spoken Arabic Number Recognition Based on Developed Ant Lion Algorithm

Ramo¹,

Younis²

2021

IJC

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“…In [26], the author proposed enhanced Ant lion Optimizer along with Artificial Neural Network. This research focused on predicting Chinese Influenza.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimized Component based Selection using LSTM Model by Integrating Hybrid MVO-PSO Soft Computing Technique

Banga¹,

Bhatia²

2021

Adv. sci. technol. eng. syst. j.

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Research focused on training and testing of dataset afterOptimizing Software Component with the help of deep neural network mechanism. Optimized components are selected for training and testing to improve the accuracy at the time of software selection. Selected components are required to be attuned and accommodating as per requirement. Soft computing mechanism such as PSO and MVO will be used for optimization. Deep Neural-Network mechanism is performing training and testing to get the confusion metrics of true positive/negative and false positive/negative. The accuracy, precision, recall value and fscore are computed to assure accuracy of proposed work. The proposed mechanism is making use of LSTM layer for more accurate output. Proposed research is exploring inadequacy of existing research and extent of incorporation of previous mechanism to soft computing mechanism in CBSE.

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“…Then, the search for expression (1) [or equivalent expression (2)], which would correctly reproduce values of the output factor y(t), is reduced to the search for the exponents δ (i) j in the productsX i (t). We note that this is a typical optimization problem [12][13][14][15]. In the case when the number of the input factors is not large, such problems are solved by the so called brute force method [16].…”

Section: Description Of the Approachmentioning

confidence: 99%

Formation of Regression Model for Analysis of Complex Systems Using Methodology of Genetic Algorithms

Мокшин

Mokshin

Mirziyarova

2020

Nonlinear Phenomena in Complex Systems

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This study presents the approach to analyze evolution of an arbitrary complex system whose behavior is characterized by a set of different time-dependent factors. The key requirement for these factors is that they must contain an information about the system only; it does not matter at all what the nature (physical, biological, social, economic, etc.) of a complex system is. Within the framework of the presented theoretical approach, the problem of searching for non-linear regression models that express the relationship between these factors for a complex system under study is solved. It will be shown that this problem can be solved using the methodology of genetic (evolutionary) algorithms. The resulting regression models make it possible to predict the most probable evolution of the considered system, as well as to determine the significance of some factors and, thereby, to formulate some recommendations to drive by this system. It will be shown that the presented theoretical approach can be used to analyze data (information) characterizing the educational process in the discipline"Physic" in the secondary school, and to develop the strategies for improving academic performance in this discipline.

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The Improved Antlion Optimizer and Artificial Neural Network for Chinese Influenza Prediction

Cited by 23 publications

References 39 publications

A Novel Approach to Spoken Arabic Number Recognition Based on Developed Ant Lion Algorithm

A Novel Approach to Spoken Arabic Number Recognition Based on Developed Ant Lion Algorithm

Optimized Component based Selection using LSTM Model by Integrating Hybrid MVO-PSO Soft Computing Technique

Formation of Regression Model for Analysis of Complex Systems Using Methodology of Genetic Algorithms

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