Model Order Reduction by Legendre Expansion Using Harmony Search Algorithm by Hasan Nasiri Soloklo, Malihe Maghfoori Farsangi

Subjects: “…Harmony search algorithm…”
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MIMO System Reduction Using Modified Pole Clustering and Genetic Algorithm by C. B. Vishwakarma, R. Prasad

“…This method guarantees stability of the reduced model if the original high-order system is stable. The algorithm of the proposed method is illustrated with the help of an example and the results are compared with the other well-known reduction techniques.…”
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Optimizing Lattice Basis Reduction Algorithm on ARM V8 Processors by Ronghui Cao, Julong Wang, Liming Zheng, Jincheng Zhou, Haodong Wang, Tiaojie Xiao, Chunye Gong

“…The LLL (Lenstra–Lenstra–Lovász) algorithm is an important method for lattice basis reduction and has broad applications in computer algebra, cryptography, number theory, and combinatorial optimization. …”
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Efficient PAPR reduction algorithm in OFDM based on nonlinear piecewise companding by Zhitong XING, Yun LI, Deyi PENG, Bensi ZHANG, Kaiming LIU, Yuan’an LIU

“…Focusing on the high peak-to-average power ratio （PAPR） problem in orthogonal frequency division multiplexing （OFDM） systems， a generalized hybrid of rayleigh and sine distribution based nonlinear companding algorithm for PAPR reduction in OFDM systems was provided.For the proposed algorithm， signal samples with small amplitudes remain unchanged.For the signal samples with large amplitudes， their probability density function were changed from rayleigh distribution to sine-based distribution.The proposed algorithm can effectively reduce the PAPR， and at the same time， maintain the bit error rate performance and power spectral density performance.Simulation results indicate that with the same PAPR performance， compared with referred companding schemes， the proposed algorithm has lower bit error rate and out of band radiation.…”
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GENETIC ALGORITHM-PID CONTROLLER FOR MODEL ORDER REDUCTION PANTOGRAPHCATENARY SYSTEM by Nasir A. Al-Awad, Izz K. Abboud, Muaayed F. Al-Rawi

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N-Dimensional Reduction Algorithm for Learning from Demonstration Path Planning by Juliana Manrique-Cordoba, Miguel Ángel de la Casa-Lillo, José María Sabater-Navarro

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Reduction algorithm based on supervised discriminant projection for network security data by Fangfang GUO, Hongwu LYU, Weilin REN, Ruini WANG

“…In response to the problem that for dimensionality reduction, traditional manifold learning algorithm did not consider the raw data category information, and the degree of clustering was generally at a low level, a manifold learning dimensionality reduction algorithm with supervised discriminant projection (SDP) was proposed to improve the dimensionality reduction effects of network security data.On the basis of the nearest neighbor matrix, the label information of the raw data category was exploited to construct a supervised discriminant matrix in order to translate unsupervised popular learning into supervised learning.The target was to find a low dimensional projective space with both maximum global divergence matrix and minimum local divergence matrix, ensuring that the same kind of data was concentrated and heterogeneous data was scattered after dimensionality reduction projection.The experimental results show that the SDP algorithm, compared with the traditional dimensionality reduction algorithms, can effectively remove redundant data with low time complexity.Meanwhile the data after dimensionality reduction is more concentrated, and the heterogeneous samples are more dispersed, suitable for the actual network security data analysis model.…”
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A Fast Hybrid Classification Algorithm with Feature Reduction for Medical Images by Hanan Ahmed Hosni Mahmoud, Abeer Abdulaziz AlArfaj, Alaaeldin M. Hafez

“…In this paper, we are introducing a fast hybrid fuzzy classification algorithm with feature reduction for medical images. …”
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Application of Machine Learning for Predictive Analysis and Management of Mediterranean-Farmed Fish Mortalities: A Risk Management Case Study Using Apache Spark by Marios C. Gkikas, Dimitris C. Gkikas, Gerasimos Vonitsanos, John A. Theodorou, Spyros Sioutas

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Predictive analytics of complex healthcare systems using deep learning based disease diagnosis model by Muhammad Kashif Saeed, Alanoud Al Mazroa, Bandar M. Alghamdi, Fouad Shoie Alallah, Abdulrhman Alshareef, Ahmed Mahmud

“…This manuscript proposes the Predictive Analytics of Complex Healthcare Systems Using the DL-based Disease Diagnosis Model (PACHS-DLBDDM) method. …”
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Predicting student retention: A comparative study of machine learning approach utilizing sociodemographic and academic factors by Reymark D. Deleña, Norniña J. Dia, Redeemtor R. Sacayan, Joseph C. Sieras, Suhaina A. Khalid, Amer Hussien T. Macatotong, Sacaria B. Gulam

“…This study explores the predictive potential of machine learning (ML) algorithms in identifying students at risk of dropping out using historical academic and sociodemographic data from Mindanao State University–Main Campus, covering a ten-year period (2012–2022). …”
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A Review of Reliability Assessment and Lifetime Prediction Methods for Electrical Machine Insulation Under Thermal Aging by Jian Zhang, Jiajin Wang, Hongbo Li, Qin Zhang, Xiangning He, Cui Meng, Xiaoyan Huang, Youtong Fang, Jianwei Wu

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ON DESIGN OF PREDICTIVE MODEL FOR HEART DISEASE by Soumyendu Bhattacharjee, Susmita Das, Sangita Roy, Arpita Santra, Anasuya Sarkar, Moumita Pa, Biswarup Neogi

“…We create a coronary disease prediction model based on the patient's clinical history to assess whether or not the patient is most likely to develop a coronary illness. …”
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Transformer–BiLSTM Fusion Neural Network for Short-Term PV Output Prediction Based on NRBO Algorithm and VMD by Xiaowei Fan, Ruimiao Wang, Yi Yang, Jingang Wang

“…And finally, the VMD-NRBO-Transformer-BiLSTM prediction model and hyperparameter selection are evaluated by the NRBO algorithm. …”
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Prediction of Chlorophyll-a Concentration Distribution Using Generative Adversarial Network (GAN) Algorithm on Processed Remote Sensing Images by Wattaqwa Amira Zul’Ilmi, Jaya Indra, Iqbal Muhammad

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A Meta-Heuristic Algorithm-Based Feature Selection Approach to Improve Prediction Success for Salmonella Occurrence in Agricultural Waters by Murat Canayaz, Murat Demir, Zeynal Topalcengiz

“…Recently, the performances of various algorithms have been tested for the prediction of indicator bacteria population and pathogen occurrence in agricultural water sources. …”
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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

“…Optimizing soil nutrient prediction models is important for achieving maximum agricultural output and sustainability while also ensuring effective resource management and environmental protection, as demonstrated by a case study in Johannesburg, South Africa. …”
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Applying genetic algorithm to extreme learning machine in prediction of tumbler index with principal component analysis for iron ore sintering by Senhui Wang

“…The results showed that an improvement in predictive accuracy can be obtained by the GA-ELM approach, and the accuracy of TI prediction is 81.85% for absolute error under 0.7%.…”
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Prediction of train wheel diameter based on Gaussian process regression optimized using a fast simulated annealing algorithm. by Xiaoying Yu, Hongsheng Su, Zeyuan Fan, Yu Dong

“…An algorithm to predict train wheel diameter based on Gaussian process regression (GPR) optimized using a fast simulated annealing algorithm (FSA-GPR) is proposed in this study to address the problem of dynamic decrease in wheel diameter with increase in mileage, which affects the measurement accuracy of train speed and location, as well as the hyper-parameter problem of the GPR in the traditional conjugate gradient algorithm. …”
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Prediction of Crop Yield by Support Vector Machine Coupled with Deep Learning Algorithm Procedures in Lower Kulfo Watershed of Ethiopia by Abebe Temesgen Ayalew, Tarun Kumar Lohani

“…Sensible and judicious utilization of water for agriculture in conjunction with prediction techniques increases the crop yield. The Ethiopian economy relies on and is exclusively dependent on agricultural-based activities. …”
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