Suchergebnisse - Computing methodologies Machine learning Machine learning approaches Bio-inspired approaches

Hybridizing extreme learning machine and bio-inspired computing approaches for improved stock market forecasting von Gocken, Mustafa, Boru, Asli, Dosdogru, Ayse Tugba, Ozcalici, Mehmet

“… In this context, bio-inspired computing approaches including evolutionary computation and swarm intelligence can be used to make more accurate calculations and forecasting results …”
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Improved bio-inspired with machine learning computing approach for thyroid prediction von Kesavulu, Divya, R, Kannadasan

“… -being. This study investigates the use of several machine learning (ML) and deep learning (DL) methods, such as random forest (RF …”
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Bio-inspired computing and Machine learning analytics for ac future-oriented mental well-being von Chakraborty, Chinmay, Unhelkar, Bhuvan, Mahmoudi, Saïd

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Bio-inspired computing and Machine learning analytics for a future-oriented mental well-being von Chakraborty, Chinmay, Unhelkar, Bhuvan, Mahmoudi, Saïd

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Bio-inspired computing and Machine learning analytics for future-oriented mental well-being von Chakraborty, Chinmay, Unhelkar, Bhuvan, Mahmoudi, Saïd

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Bio-inspired EEG signal computing using machine learning and fuzzy theory for decision making in future-oriented brain-controlled vehicles von Byeon, Haewon, Quraishi, Aadam, Khalaf, Mohammed I., MP, Sunil, Khan, Ihtiram Raza, Dutta, Ashit Kumar, Dasari, Rakeshnag, Yellu, Ramswaroop Reddy, Reegu, Faheem Ahmad, Bhatt, Mohammed Wasim

“… One kind of autonomous vehicle that can take instructions from the driver by reading their electroencephalogram (EEG) signals using a Brain-Computer Interface …”
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Efficient Handoff Detection for Computation Offloading using Machine Learning and Bio-Inspired Optimization Techniques in Mobile Edge Computing von Joshi, Vaishali, Patil, Kishor

“… With the rise of smartphones and the Internet of Things (IoT), more and more calculations are being performed on mobile devices, which rapidly depletes their …”
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Bio-Inspired Machine Learning Approach to Type 2 Diabetes Detection von Al-Tawil, Marwan, Mahafzah, Basel A., Al Tawil, Arar, Aljarah, Ibrahim

“… This can be accomplished by analyzing medical datasets using data mining and machine-learning techniques …”
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insideOut: A Bio-Inspired Machine Learning Approach to Estimating Posture in Robots Driven by Compliant Tendons von Hagen, Daniel A., Marjaninejad, Ali, Loeb, Gerald E., Valero-Cuevas, Francisco J.

“… Here we propose a novel machine learning algorithm to accurately estimate joint posture during dynamic tasks by limited training of an artificial neural network (ANN …”
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Learning from errors: A bio-inspired approach for hypothesis-based machine learning von Gamrad, Dennis, Soffker, Dirk

“… This contribution present an approach extending existing learning strategies based on Situation-Operator-Modeling (SOM …”
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Prediction of EDMed micro-hole quality characteristics using hybrid bio-inspired machine learning-based predictive approaches von Rao, Thella Babu

“… In this investigation, predictive models based on bio-inspired intelligent hybrid machine learning algorithms are proposed for machining micro-holes with accurate dimensions on Inconel 718 superalloy by µEDM process …”
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A novel approach for human diseases prediction using nature inspired computing & machine learning approach von MunishKhanna, Singh, Law Kumar, Garg, Hitendra

“… Globally, patients with diabetes, diabetic retinopathy, cancer, and heart disease are growing rapidly in developed and developing countries. As a result of …”
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Free vibration behaviour of bio-inspired helicoidal laminated composite panels of revolution under thermal conditions: Multi-output machine learning approach von Garg, Aman, Li, Li, Zheng, Weiguang, Belarbi, Mohamed-Ouejdi, Raman, Roshan

“… The present work aims to study the free vibration behaviour of bio-inspired helicoidal laminated composite spherical, toroid, and conical shell panels using a single-output Support Vector Machine (SVM …”
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Prediction models for marshall mix parameters using bio-inspired genetic programming and deep machine learning approaches: A comparative study von Althoey, Fadi, Akhter, Muhammad Naveed, Nagra, Zohaib Sattar, Awan, Hamad Hassan, Alanazi, Fayez, Khan, Mohsin Ali, Javed, Muhammad Faisal, Eldin, Sayed M., Özkılıç, Yasin Onuralp

“… This research study utilizes four machine learning techniques, i.e., Multi Expression programming (MEP …”
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Nature-inspired computing and machine learning based classification approach for glaucoma in retinal fundus images von Singh, Law Kumar, Khanna, Munish, Thawkar, Shankar, Singh, Rekha

“… In addition, computer-assisted diagnosis (CAD) systems can be created to solve these obstacles by using machine learning approaches to classify retinal pictures as "healthy" or "infected …”
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Exploring the performance and emission characteristics of a dual fuel CI engine using microalgae biodiesel and diesel blend: a machine learning approach using ANN and response surface methodology von Tiwari, Chandrabhushan, Dwivedi, Gaurav, Verma, Tikendra Nath

“… The study employs a machine-learning (ML) approach, integrating artificial neural networks (ANN …”
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Large-scale classification of metagenomic samples: a comparative analysis of classical machine learning techniques vs a novel brain-inspired hyperdimensional computing approach von Joshi, Jayadev, Cumbo, Fabio, Blankenberg, Daniel

“… Classical machine learning techniques have revolutionized bioinformatics, enabling researchers to extract knowledge from complex biological data …”
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GENESYS: A novel evolutionary program synthesis tool with continuous optimization von Mandal, Shantanu, Anderson, Todd A, Turek, Javier, Gottschlich, Justin, Muzahid, Abdullah

“… Most existing approaches formulate program synthesis as a search problem with discrete parameters …”
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PertNAS: Architectural Perturbations for Memory-Efficient Neural Architecture Search von Ahmad, Afzal, Xie, Zhiyao, Zhang, Wei

“… This leads to GPU-memory bottlenecks that hamper the algorithm's scalability. To resolve these bottlenecks, we propose a perturbations-based evolutionary approach …”
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UniGenCoder: Merging SEQ2SEQ and SEQ2TREE Paradigms for Unified Code Generation von Shao, Liangying, Yan, Yanfu, Poshyvanyk, Denys, Su, Jinsong

“… Deep learning-based code generation has completely transformed the way developers write programs today …”
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