A Trombe wall-heating system is used to absorb solar energy to heat *** parameters affect the system performance for optimal *** study evaluated the performance of four machine learning algorithms—linear regression,k...
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A Trombe wall-heating system is used to absorb solar energy to heat *** parameters affect the system performance for optimal *** study evaluated the performance of four machine learning algorithms—linear regression,k-nearest neighbors,random forest,and decision tree—for predicting the room temperature in a Trombe wall *** accuracy of the algorithms was assessed using R^(2)and root mean squared error(RMSE)*** results demonstrated that the k-nearest neighbors and random forest algorithms exhibited superior performance,with R^(2)and RMSE values of 1 and *** contrast,linear regression and decision tree showed weaker *** findings highlight the potential of advanced machine learning algorithms for accurate room temperature prediction in Trombe wall systems,enabling informed design decisions to enhance energy efficiency.
Recently,deep learning(DL)became one of the essential tools in bioinformatics.A modified convolutional neural network(CNN)is employed in this paper for building an integratedmodel for deoxyribonucleic acid(DNA)*** any...
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Recently,deep learning(DL)became one of the essential tools in bioinformatics.A modified convolutional neural network(CNN)is employed in this paper for building an integratedmodel for deoxyribonucleic acid(DNA)*** any CNN model,convolutional layers are used to extract features followed by max-pooling layers to reduce the dimensionality of features.A novel method based on downsampling and CNNs is introduced for feature *** downsampling is an improved form of the existing pooling layer to obtain better classification *** two-dimensional discrete transform(2D DT)and two-dimensional random projection(2D RP)methods are applied for *** convert the high-dimensional data to low-dimensional data and transform the data to the most significant feature ***,there are parameters which directly affect how a CNN model is *** this paper,some issues concerned with the training of CNNs have been *** CNNs are examined by changing some hyperparameters such as the learning rate,size of minibatch,and the number of *** and assessment of the performance of CNNs are carried out on 16S rRNA bacterial *** results indicate that the utilization of a CNN based on wavelet subsampling yields the best trade-off between processing time and accuracy with a learning rate equal to 0.0001,a size of minibatch equal to 64,and a number of epochs equal to 20.
Advances in algorithmic studies have been made recently, especially in the area of finding the shortest path. Despite taking a greedy approach, the Dijkstra algorithm is well recognized for its efficacy and has establ...
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Interest in Wireless LAN 802.11 is climbing owing to its cost-effectiveness and simplicity of installation, yet its restricted Quality of Service (QoS) capabilities present obstacles for real-time apps. This endeavour...
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Detecting healthy arecanut leaves, yellow leaf disease in arecanut, and differentiating these from other types of leaves using deep learning involves designing an advanced neural network model for precise image classi...
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Biomedical image analysis plays a crucial role in the early and accurate diagnosis of diseases, significantly impacting patient outcomes. This study presents an innovative approach to biomedical image analysis by inte...
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The task of identifying key skills from job vacancies descriptions is considered in the article. The source data consists of vacancy texts from the 'Jobs in Russia' portal, in which skill-related entities were...
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Artificial intelligence has become like-humans in thinking and interpretations. But its uses are still limited and are viewed as black boxes, and this is the most important factor underlying the limited applications, ...
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Chronic Kidney Disease (CKD) is a common disease worldwide that is manifested by slow progressive loss of kidney function that can result in complications and kidney failure. That is why conventional approaches to CKD...
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In the last few decades, metaheuristic algorithms that use the laws of nature have been used dramatically in numerous and complex optimization problems. The artificial hummingbird algorithm (AHA) is one of the metaheu...
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