Computational Intelligence
Swarm intelligent algorithms have the ability to quickly find optimal solutions to problems, but they suffer from an imbalance between global exploration and local exploitation. The dung beetle optimization (DBO) algorithm was newly developed in 2022 and has excellent comprehensive performance; however, it still suffers from this problem.
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200 Views
<p>Time-of-use (ToU) tariffs flexibly offer cheaper electricity prices to industrial and residential users during off-peak periods, encouraging them to shift their peak electricity demands in valley periods. Flow Shop Scheduling (FSS) model is one of the most prevalent models in manufacturing. To explore the significant role of ToU tariffs in manufacturing, this study addresses a novel bi-objective FSS problem under ToU tariffs.</p>
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45 Views
In the domain of Natural Language Processing (NLP), the English Writing Fluency Improvement for non-native speakers, particularly in academic contexts, poses significant challenges. While Sentence-level Revision (SentRev) endeavors to address this concern, the existing evaluation corpus, SMITH, falls short in offering a robust and comprehensive assessment of the task. To bridge this gap, our research offers a novel evaluation corpus generation scheme, leading to the creation of Ten-Country Non-native Academic English Corpus (TCNAEC).
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58 Views
We have obtained data from May 2022 to October 2023 for our suggested framework modelling. This set of data incorporates seasonality-related speech, which we convert into text, Facebook, and Twitter posts. On the whole, 4646 data elements have been acquired, comprising 3716 representing affected individuals and the remainder of 930 representing unaffected individuals, which generated a proportional 4:1 ratio.
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452 Views
For coil dataset，the shape of one data is [160,160,5]
For transformer dataset，the shape of one data is [400,400,5]
For IPM motor dataset，the shape of one data is [180,180,5]
The first five layers consist of input device property information, while the sixth layer represents the FEA magnetic field distribution results.
When using, please note to split the dataset into two parts, with x being transformed as follows:
X = data[:, :, :5]
X = np.transpose(X, (2, 0, 1))
X = torch.from_numpy(X)
, and y being transformed as follows:
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312 Views
This data set comes from the MetaFilter website. The question ID data of the askme section is obtained through the official dump data. After selecting a specific category, the corresponding other data is obtained using the ID, including the question title, description, questioner, tags, and all comments.
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28 Views
SSADMO algorithm is proposed to study the optimal spatial trajectories of sea buckthorn fruit vibration separation. In this study, kinematics interpolation analysis of manipulator trajectories was carried out to compare the trajectories of cubic polynomials and quintic polynomial interpolation, and to compare the trajectories and attitudes of the manipulators under the condition of limited operating range and speed, in this paper, we propose a new SSADMO algorithm which combines the advantages of SSA and DMO optimization algorithms in the 3-5-3 polynomial interpolation.
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29 Views
Social Media Big Dataset for Research, Analytics, Prediction, and Understanding the Global Climate Change Trends is focused on understanding the climate science, trends, and public awareness of climate change. The use of dataset for analytics of climate change trends greatly helps in researching and comprehending global climate change trends.
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3875 Views
The Numerical Latin Letters (DNLL) dataset consists of Latin numeric letters organized into 26 distinct letter classes, corresponding to the Latin alphabet. Each class within this dataset encompasses multiple letter forms, resulting in a diverse and extensive collection. These letters vary in color, size, writing style, thickness, background, orientation, luminosity, and other attributes, making the dataset highly comprehensive and rich.
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498 Views
The instantaneous state (situation) of the game was constituted by four values: the cart position, the cart speed, the pole angle to the vertical axis, and the pole angular velocity.
For each action taken by the human player in the game, a tuple containing the four values representing the current game situation, along with the action and reward obtained (utility), is recorded as a situation-decision-utility (SDU) tuple.
3 types of actions have been recorded: Move left (-1), move rght (1) and no action (0).
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21 Views