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Heuristics

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Wild Geese Migration Optimization Algorithm: A New Meta-Heuristic Algorithm for Solving Inverse Kinematics of Robot.

Computational intelligence and neuroscience
This paper proposes a new meta-heuristic algorithm, named wild geese migration optimization (GMO) algorithm. It is inspired by the social behavior of wild geese swarming in nature. They maintain a special formation for long-distance migration in smal...

Optimizing Deep Learning Model for Software Cost Estimation Using Hybrid Meta-Heuristic Algorithmic Approach.

Computational intelligence and neuroscience
Effective software cost estimation significantly contributes to decision-making. The rising trend of using nature-inspired meta-heuristic algorithms has been seen in software cost estimation problems. The constructive cost model (COCOMO) method is a ...

Artificial Intelligence System Detection in English Teaching Based on Heuristic Genetic Algorithm.

Computational intelligence and neuroscience
Using the traditional English teaching mode is difficult to help correct students, and it is difficult to achieve human-computer interaction in oral English communication. In order to improve the effect of English detection and improve teaching effic...

Convolutional Neural Networks and Heuristic Methods for Crowd Counting: A Systematic Review.

Sensors (Basel, Switzerland)
The crowd counting task has become a pillar for crowd control as it provides information concerning the number of people in a scene. It is helpful in many scenarios such as video surveillance, public safety, and future event planning. To solve such t...

Heuristic Attention Representation Learning for Self-Supervised Pretraining.

Sensors (Basel, Switzerland)
Recently, self-supervised learning methods have been shown to be very powerful and efficient for yielding robust representation learning by maximizing the similarity across different augmented views in embedding vector space. However, the main challe...

Exploring Orientation Invariant Heuristic Features with Variant Window Length of 1D-CNN-LSTM in Human Activity Recognition.

Biosensors
Many studies have explored divergent deep neural networks in human activity recognition (HAR) using a single accelerometer sensor. Multiple types of deep neural networks, such as convolutional neural networks (CNN), long short-term memory (LSTM), or ...

Computational Scientific Discovery in Psychology.

Perspectives on psychological science : a journal of the Association for Psychological Science
Scientific discovery is a driving force for progress involving creative problem-solving processes to further our understanding of the world. The process of scientific discovery has historically been intensive and time-consuming; however, advances in ...

Artificial intelligence-informed planning for the rapid response of hazard-impacted road networks.

Scientific reports
Post-hazard rapid response has emerged as a promising pathway towards resilient critical infrastructure systems (CISs). Nevertheless, it is challenging to scheme the optimal plan for those rapid responses, given the enormous search space and the hard...

Individualized Short-Term Electric Load Forecasting Using Data-Driven Meta-Heuristic Method Based on LSTM Network.

Sensors (Basel, Switzerland)
Short-term load forecasting is viewed as one promising technology for demand prediction under the most critical inputs for the promising arrangement of power plant units. Thus, it is imperative to present new incentive methods to motivate such power ...

Mapping of groundwater salinization and modelling using meta-heuristic algorithms for the coastal aquifer of eastern Saudi Arabia.

The Science of the total environment
The growing increase in groundwater (GW) salinization in the coastal aquifers has reached an alarming socio-economic menace in Saudi Arabia and various places globally due to several natural and anthropogenic activities. Hence, evaluating the GW sali...