Swarm-based hybrid optimization algorithms: an exhaustive analysis and its applications to electricity load and price forecasting.

In this work, we intend to propose multiple hybrid algorithms with the idea of giving a choice to the particles of a swarm to update their position for the next generation. To implement this concept, Cuckoo Search Algorithm (CSA), Grey Wolf Optimization (GWO), Harris Hawks Optimization (HHO), and Whale Optimization Algorithm (WOA) have been utilized. Exhaustive possible combinations of these algorithms are developed and benchmarked against the base algorithms. These hybrid algorithms have been validated on twenty-four well-known unimodal and multimodal benchmarks functions, and detailed analysis with varying dimensions and population size is discussed for the same. Further, the efficacy of these algorithms has been tested on short-term electricity load and price forecasting applications. For this purpose, the algorithms have been combined with Artificial Neural Networks (ANNs) to evaluate their performance on the ISO New Pool England dataset. The results demonstrate that hybrid optimization algorithms perform superior to their base algorithms in most test cases. Furthermore, the results show that the performance of CSA-GWO is significantly better than other algorithms.

In situ decomposition of crop residues using lignocellulolytic microbial consortia: a viable alternative to residue burning.

Open field burning of crop residue causes severe air pollution and greenhouse gas emission contributing to global warming. In order to seek an alternative, the current study was initiated to explore the prospective of lignocellulolytic microbes to expedite in situ decomposition of crop residues. Field trials on farmers' field were conducted in the state of Haryana and Maharashtra, to target the burning of rice and wheat residue and sugarcane trash, respectively. A comparative study among crop residue removal (CRR), crop residue burning (CRB) and in situ decomposition of crop residues (IND) revealed that IND of rice and wheat residues took 30 days whereas IND of sugarcane trash took 45 days. The decomposition status was assessed by determining the initial and final lignin to cellulose ratio which increased significantly from 0.23 to 0.25, 0.21 to 0.23 and 0.24 to 0.27 for rice, wheat residues and sugarcane trash, respectively. No yield loss was noticed in IND for both rice-wheat system and sugarcane-based system; rather IND showed relatively better crop yield as well as soil health parameters than CRB and CRR. Furthermore, the environmental impact assessment of residue burning indicated a substantial loss of nutrients (28-31, 23-25 and 51-77 kg ha-1 of N+P2O5+K2O for rice, wheat and sugarcane residue) as well as the emission of pollutants to the atmosphere. However, more field trials, as well as refinement of the technology, are warranted to validate and establish the positive potential of in situ decomposition of crop residue to make it a successful solution against the crop residue burning.