AIMC Topic: Computer Heuristics

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Solving water scarcity challenges in arid regions: A novel approach employing human-based meta-heuristics and machine learning algorithm for groundwater potential mapping.

Chemosphere
Addressing water scarcity challenges in arid regions is a pressing concern and demands innovative solutions for accurate groundwater potential mapping (GPM). This study presents a comprehensive evaluation of advanced modeling techniques to enhance th...

Optimal Task Allocation Algorithm Based on Queueing Theory for Future Internet Application in Mobile Edge Computing Platform.

Sensors (Basel, Switzerland)
For 5G and future Internet, in this paper, we propose a task allocation method for future Internet application to reduce the total latency in a mobile edge computing (MEC) platform with three types of servers: a dedicated MEC server, a shared MEC ser...

Breast Cancer Diagnosis by Convolutional Neural Network and Advanced Thermal Exchange Optimization Algorithm.

Computational and mathematical methods in medicine
A common gynecological disease in the world is breast cancer that early diagnosis of this disease can be very effective in its treatment. The use of image processing methods and pattern recognition techniques in automatic breast detection from mammog...

A heuristic, computer-driven and top-down approach to identify novel bioactive peptides: A proof-of-principle on angiotensin I converting enzyme inhibitory peptides.

Food research international (Ottawa, Ont.)
Bioactive peptides are short peptides (3-20 amino acid residues in length) endowed of specific biological activities. The identification and characterization of bioactive peptides of food origin are crucial to better understand the physiological cons...

A Hybrid Method to Predict Postoperative Survival of Lung Cancer Using Improved SMOTE and Adaptive SVM.

Computational and mathematical methods in medicine
Predicting postoperative survival of lung cancer patients (LCPs) is an important problem of medical decision-making. However, the imbalanced distribution of patient survival in the dataset increases the difficulty of prediction. Although the syntheti...

Many-objective BAT algorithm.

PloS one
In many objective optimization problems (MaOPs), more than three distinct objectives are optimized. The challenging part in MaOPs is to get the Pareto approximation (PA) with high diversity and good convergence. In Literature, in order to solve the i...

Extractive single document summarization using binary differential evolution: Optimization of different sentence quality measures.

PloS one
With the increase in the amount of text information in different real-life applications, automatic text-summarization systems become more predominant in extracting relevant information. In the current study, we formulated the problem of extractive te...

A Comprehensive Network Atlas Reveals That Turing Patterns Are Common but Not Robust.

Cell systems
Turing patterns (TPs) underlie many fundamental developmental processes, but they operate over narrow parameter ranges, raising the conundrum of how evolution can ever discover them. Here we explore TP design space to address this question and to dis...

A novel bio-heuristic computing algorithm to solve the capacitated vehicle routing problem based on Adleman-Lipton model.

Bio Systems
DNA computing, as one of potential means to solve complicated computational problems, is a new field of interdisciplinary research, including computational mathematics, parallel algorithms, bioinformatics. Capacitated vehicle routing problem is one o...

Simple Hyper-Heuristics Control the Neighbourhood Size of Randomised Local Search Optimally for LeadingOnes.

Evolutionary computation
Selection hyper-heuristics (HHs) are randomised search methodologies which choose and execute heuristics during the optimisation process from a set of low-level heuristics. A machine learning mechanism is generally used to decide which low-level heur...