Using Particle Swarm Optimization to Accurately Identify Syntactic Phrases in Free Text

Tambouratzis, George

doi:10.1515/jaiscr-2018-0004

Cited by 19 publications

(5 citation statements)

References 25 publications

(28 reference statements)

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“…Traditional teaching methods focus on language form and try to control and minimize the possibility of grammatical errors without paying enough attention to language. Grammatical complexity gradually causes educators and teachers and many language output evaluation schemes to begin to emphasize the requirements of complexity and change [11]. According to syntactic complexity and semantic coherence, it should help the researchers constantly observe and provide a theoretical framework for interpretation; it should lay the foundation for replication and accumulation of experience and understanding of important structures.…”

Section: Introductionmentioning

confidence: 99%

Analysis of Syntactic Complexity and Semantic Coherence of Academic English Writing Based on Particle Swarm Optimization

2022

Mobile Information Systems

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Writing is an important part of testing language ability, and it is urgent to find some objective indicators to determine and evaluate the surface language structure, which will help language learners’ better master the target language. Complexity and semantic coherence are considered to be an important factor in the teaching of second language writing. In practice, due to the complexity of English writing syntax, such as a large number of high-dimensional nonlinear optimization problems, a new intelligent evaluation method is needed to solve them. At present, particle swarm optimization (PSO) has been widely used in function optimization, neural network training, combinatorial optimization, and other fields. This paper studies the syntactic complexity and semantic coherence of academic English writing based on PSO. The number of phrases is related to writing achievement. When the number of experiments reaches 25, the significant values of syntactic complexity and semantic coherence of data mining algorithm, artificial intelligence algorithm, decision tree algorithm, and PSO algorithm are 0.008, 0.003, 0.002, and 0.013, respectively, which shows that PSO algorithm is the best among them.

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Section: Introductionmentioning

confidence: 99%

Analysis of Syntactic Complexity and Semantic Coherence of Academic English Writing Based on Particle Swarm Optimization

2022

Mobile Information Systems

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“…According to Zhang et al [43], PSO is one of the most commonly used optimization algorithms. It has been widely applied in numerous areas, owing to its simple algorithm and short computation time [44,45]. In this study, the PSO algorithm with relatively fast computation time was employed, considering the characteristics of MPC in which the operation strategy for the following day must be rapidly established.…”

Section: Mpc Simulationmentioning

confidence: 99%

LSTM-Based Model Predictive Control for Optimal Temperature Set-Point Planning

Jeon

Kim

2021

Sustainability

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The growing interest in saving building energy has increasingly motivated studies on model predictive control (MPC), where system operation proceeds according to a planned operation strategy. Data-driven models that perform learning using past operation data of buildings are favorable for MPC applications owing to their fast computation speed. However, it is difficult to apply MPC to buildings with insufficient operation data, as the prediction accuracy varies depending on the data used for learning. To address this, we propose a method that involves generating data through a detailed building energy model and utilizing a long short-term memory (LSTM) network that performs learning using the data as an MPC model. The model was verified through a comparison with the reference model using the same optimization algorithm. In the MPC of the objective function, which is to reduce electrical energy expenditure by optimizing the indoor temperature of the target building, approximately 35% grid energy consumption was reduced compared to a reference case, by increasing self-consumption of photovoltaic (PV) energy and avoiding PV curtailment. Further, the required computation time was reduced to approximately 30%, even including the data generation time for daily learning, thereby confirming the feasibility of the MPC model that employs LSTM.

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“…The GP algorithm is based on a typical schema of a population-based algorithm (see e.g. [2,42,43,49]). It uses two populations, i.e.…”

Section: Description Of the Proposed Gp Algorithmmentioning

confidence: 99%

Genetic Programming Algorithm for Designing of Control Systems

Cpałka¹,

Łapa²,

Przybył³

2018

ITC

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,andrzej.przybyl}@iisi.pcz.pl Genetic programming algorithms and other population-based methods are a convenient tool for solving complex interdisciplinary problems. Their characteristic feature is that they flexibly adapt to the problem and expectations of a designer. In this paper, they are used for designing complex control systems. In particular, a new approach for automatic designing of PID-based controllers which are resistant to noises in the measuring path is proposed. It is based on the knowledge about an object model and capabilities of the genetic algorithm and genetic programming. Not only do these make it possible to tune parameters and select the structure of PID-based controllers, but they also tune parameters of some additional components of a complex controller structure, like parameters of finite impulse response (FIR) filters. The idea of the proposed approach relies on proper encoding of the controller and a dedicated way of evolutionary processing of encoded solutions. The approach proposed in this paper has been tested using a typical control problem, i.e. a DC motor control problem.

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Using Particle Swarm Optimization to Accurately Identify Syntactic Phrases in Free Text

Cited by 19 publications

References 25 publications

Analysis of Syntactic Complexity and Semantic Coherence of Academic English Writing Based on Particle Swarm Optimization

Analysis of Syntactic Complexity and Semantic Coherence of Academic English Writing Based on Particle Swarm Optimization

LSTM-Based Model Predictive Control for Optimal Temperature Set-Point Planning

Genetic Programming Algorithm for Designing of Control Systems

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