In this paper, we proposed a modified KOS-ELM algorithm with forgetting mechanism (KOS-ELMF) to deal with the time-sensitive applications. A sliding window is applied to limit the active training data in order to 'forget' the old observations. The size of the sliding window can change ...
The window best matched is made to participate in the process of predicting weather conditions. The prediction is made based on sliding window algorithm. The monthwise results are being computed for three years to check the accuracy. The results of the approach suggested that the method used for...
Algorithm: The implementation of Trie Tree (C++) Question: There is a text file which includes many lines. And each line has only one word or phrase. Now, please implement a program to get the prefix of each word. (Please print each of prefix word b... ...
In this section, the proposed FP mining algorithm is introduced. The algorithm model framework is primarily divided into five parts, as shown in Fig.4. After the data pre-processed, they first pass through the first module, which applies the Variable-Size Window Drift Detection algorithm (VSW-...
Secondly, sliding time window technique is adopted to analyze the dynamics and trends in the carbon market. Then, differential evolution (DE) algorithm is utilized to improve the performance of support vector regression (SVR), where SVR is used as the prediction model for carbon emission trading ...
LSTM as an MSA algorithm achieved the best result based on both criteria with values of 67.6 µm and 58.5 µm, respectively. The 67.6 µm error would be translated to about 2.4% error percentage when considering the full range of drop width values in the test dataset. The evaluation ...
Compared with deep learning, which requires more powerful hardware, machine learning is faster in the training phase and actual detection. Since the labels in this experiment are relatively easy to obtain, we can use a supervised machine learning algorithm to solve this problem. In summary, our ...
classSolution {public: vector<int> maxSlidingWindow(vector<int>& nums,intk) { vector<int>ret;if(k ==0)returnret;if(k ==nums.size()) { ret.push_back(*std::max_element(nums.begin(), nums.end()));returnret; } deque<int> mq;//only store indexfor(inti =0; i < nums.size()...
While producing the right-to-left sliding window form requires a dedicated procedure, the left-to-right form can be generated “on-the-fly” during the exponentiation algorithm, combining the generation of the expansion and the exponentiation itself in one go. Consequently, the left-to-right slid...
ANNs are the basic supervised learning algorithm of deep learning. ANNs are feed forward computing systems with the task of mapping the function f between the input X and the output Y as shown in Eq. (1) (1)Y=f(X) ANNs belong to supervised learning exactly because they are to be tra...