Results 121 to 130 of about 2,657,297 (246)

Improving photovoltaic cell parameter calculations through a puffer fish inspired optimization technique

Heliyon
The precise estimation of solar PV cell parameters has become increasingly important as solar energy deployment expands. Due to the intricate and nonlinear characteristics of solar PV cells, meta-heuristic algorithms show greater promise than traditional
Manish Kumar Singla, Jyoti Gupta, Nijhawan Parag, Thakur Ekta, Teshome Goa Tella, Mohamed I. Mosaad, Safaraliev Murodbek   +6 more
doaj   +1 more source

Operationalising Circular Economy Through Social Innovation: A Systems Thinking‐Based Model for Sustainability Transitions

Sustainable Development, EarlyView.
ABSTRACT Social innovation (SI) is increasingly recognised as an important enabler of circular economy (CE) transitions. However, existing research offers limited explanation of the processes through which SI operationalises CE principles, as SI and CE have largely evolved in parallel and existing conceptualisations remain predominantly descriptive ...
Souresh Cornet, Saswat Barpanda, Marc‐Antoine Diego Guidi   +2 more
wiley   +1 more source

Meta-Learning and the Full Model Selection Problem [PDF]

, 2014
When working as a data analyst, one of my daily tasks is to select appropriate tools from a set of existing data analysis techniques in my toolbox, including data preprocessing, outlier detection, feature selection, learning algorithm and evaluation ...
Sun, Quan
core  

A Novel Approach to Energy Management in Electric Steelworks

steel research international, EarlyView.
Feed‐forward neural networks are exploited to estimate electric energy consumptions of the electric arc furnace and ladle furnace processes. The models are used to optimize production schedule so that more energy intensive grades are produced when the cost of energy is lower.
Valentina Colla, Stefano Dettori, Silvia Cateni, Marco Vannucci, Antonella Vignali, Claudio Mocci, Irene Dovichi, Davide Chionna, Lorenzo Vannini, Enrico Paluzzano, Costanzo Pietrosanti, Davide Onesti, Daniele Venier   +12 more
wiley   +1 more source

Choice Function-Based Hyper-Heuristics for Causal Discovery under Linear Structural Equation Models

Biomimetics
Causal discovery is central to human cognition, and learning directed acyclic graphs (DAGs) is its foundation. Recently, many nature-inspired meta-heuristic optimization algorithms have been proposed to serve as the basis for DAG learning.
Yinglong Dang, Xiaoguang Gao, Zidong Wang   +2 more
doaj   +1 more source

Data privacy model using blockchain reinforcement federated learning approach for scalable internet of medical things

CAAI Transactions on Intelligence Technology, EarlyView.
Abstract Internet of Medical Things (IoMT) has typical advancements in the healthcare sector with rapid potential proof for decentralised communication systems that have been applied for collecting and monitoring COVID‐19 patient data. Machine Learning algorithms typically use the risk score of each patient based on risk factors, which could help ...
Chandramohan Dhasaratha, Mohammad Kamrul Hasan, Shayla Islam, Shailesh Khapre, Salwani Abdullah, Taher M. Ghazal, Ahmed Ibrahim Alzahrani, Nasser Alalwan, Nguyen Vo, Md Akhtaruzzaman   +9 more
wiley   +1 more source

Building Blocks as Experiences in Dynamic Capacitated Arc Routing Problems

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT The dynamic capacitated arc routing problem (DCARP) aims to update the service paths of vehicles in the capacitated arc routing problem when uncertain factors deteriorate the current schedule of vehicles' services. A DCARP scenario comprises a series of DCARP instances that share similarities with each other. Therefore, optimisation experience
Hao Tong, Leandro L. Minku, Stefan Menzel, Bernhard Sendhoff, Xin Yao   +4 more
wiley   +1 more source

LLM‐Powered Data Synthesis on Blockchain for Fusion Isomerism Learning in Heterogeneous Federated Systems

CAAI Transactions on Intelligence Technology, EarlyView.
ABSTRACT Severe data starvation, architectural heterogeneity and Byzantine vulnerabilities fundamentally impede the deployment of robust multiclass classification models in decentralised edge environments. To address these intertwined challenges, we propose fusion isomerism learning (FusionIL), a secure and domain‐agnostic framework that ...
Zhihao Hao, Longbing Cao, Han Yu, Xiaoqiang Teng, Guancheng Wang, Chuanbin Zhang   +5 more
wiley   +1 more source

Integrated transmission expansion planning incorporating fault current limiting devices and thyristor-controlled series compensation using meta-heuristic optimization techniques

Scientific Reports
Transmission expansion planning (TEP) is a vital process of ensuring power systems' reliable and efficient operation. The optimization of TEP is a complex challenge, necessitating the application of mathematical programming techniques and meta-heuristics.
Abdulaziz Almalaq, Khalid Alqunun, Rabeh Abbassi, Ziad M. Ali, Mohamed M. Refaat, Shady H. E. Abdel Aleem   +5 more
doaj   +1 more source

Anchors or relational risks? Educator and psychologist narratives of attachment in child–robot relationships

British Journal of Educational Psychology, EarlyView.
Abstract Background As AI‐enabled social robots become more common in schools, children may form strong emotional bonds with them despite robots not being caregivers and lacking the capacities for “true” attachment. Given limited understanding of potential risks and safeguards, professional perspectives are needed to inform responsible design and ...
Dimitris Pnevmatikos, Panagiota Christodoulou   +1 more
wiley   +1 more source