Work on leveraging optimization with mixed learning appears on Applied Soft Computing

Work on leveraging optimization with mixed learning appears on Applied Soft Computing

Warning: preg_match_all(): Compilation failed: invalid range in character class at offset 7 in /home/fingoorg/public_html/wiomax/wp-content/plugins/papercite/papercite.php on line 551

Our work on leveraging optimization with mixed individual and social learning in cooperative group optimization (CGO) appears on Applied Soft Computing: We present CGO-AS, a generalized Ant System (AS) implemented in the framework of Cooperative Group Optimization (CGO), to show

Key Applications of the Smart IoT to Transform Transportation

Key Applications of the Smart IoT to Transform Transportation

Warning: preg_match_all(): Compilation failed: invalid range in character class at offset 7 in /home/fingoorg/public_html/wiomax/wp-content/plugins/papercite/papercite.php on line 551

The applications of the Internet of Things (IoT) have been growing dramatically in recent a few years. According to IDC, the transportation sector will be among the first to see a significant growth from the IoT, and the global IoT market in

Artificial Intelligence (AI) application by exploiting problem structure in combinatorial landscapes

Artificial Intelligence (AI) application by exploiting problem structure in combinatorial landscapes

Warning: preg_match_all(): Compilation failed: invalid range in character class at offset 7 in /home/fingoorg/public_html/wiomax/wp-content/plugins/papercite/papercite.php on line 551

We proposed an artificial intelligence (AI) application by exploiting search cues in combinatorial space. We present a method using AI techniques to solve a case of pure mathematics applications for finding narrow admissible tuples. The original problem is formulated into

Artificial Intelligence (AI) Techniques

Artificial Intelligence (AI) techniques have been applied for different applications: – Advanced Planning and Scheduling for smart and scalable urban traffic control and other applications – Machine Learning (ML) Techniques for different applications – Metaheuristic Search Strategies for different applications Some of our research work

Advanced Planning and Scheduling


Warning: preg_match_all(): Compilation failed: invalid range in character class at offset 7 in /home/fingoorg/public_html/wiomax/wp-content/plugins/papercite/papercite.php on line 551

We have worked on advanced scheduling strategies for hard computational problems (e.g., Flowshop Scheduling) and real-world applications (e.g., Smart and Scalable Urban Traffic Control). Some of them could be solved using cooperative group optimization with metaheuristic search strategies, where some of

Publications

The scientists and engineers at WIOMAX frequently create research reports and publish the results of their work in academic and industry journals and conferences. To request a copy of one of our publications or seek potential collaborations and partnerships, please